Summarization of email on a client computing device based on content contribution to an email thread using classification and word frequency considerations

ABSTRACT

Systems, methods, and computer-readable media are disclosed for enhancing an email application to automatically analyze an email thread and generate a compact content summary. The content summary is based on relative content contributions provided by the constituent email messages in the email thread. The content summary may be presented in a special window without disturbing or modifying the email thread or its constituent email messages. The distinctive content summary disclosed herein comprises certain sentences that are automatically gleaned from the email thread, analyzed relative to other sentences, and presented in a chronological sequence so that the user can quickly determine what the email thread is about and/or the current status of the conversation. The content summary is based on email weights, word weights, and intersecting sentence pairs.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationSer. No. 62/250,312, filed on Nov. 3, 2015, and entitled “SUMMARIZATIONAND PROCESSING OF EMAIL ON A CLIENT COMPUTING DEVICE BASED ON CONTENTCONTRIBUTION TO AN EMAIL THREAD”. Any and all applications, if any, forwhich a foreign or domestic priority claim is identified in theApplication Data Sheet of the present application are herebyincorporated by reference under 37 CFR 1.57.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentand/or the patent disclosure as it appears in the United States Patentand Trademark Office patent file and/or records, but otherwise reservesall copyrights whatsoever.

BACKGROUND

Businesses recognize the commercial value of their data and seekreliable, cost-effective ways to protect the information stored on theircomputer networks while minimizing impact on productivity. Businessesalso recognize the value of their employees' time in managing their dataand protecting it.

SUMMARY

Reviewing emails can be time-consuming. For example, when working acrosstime zones, one could open one's email application in the morning andfind dozens or even hundreds of email messages awaiting attention in theinbox. Even when emails are organized by thread or “conversation,” theamount of time needed to navigate a long email thread may beprohibitive, or at a minimum, undesirable. A thread or conversationcomprises emails that are related by mutual replies, e.g., at least onereply to one or more messages in the thread.

The present inventors devised techniques that automatically analyze anemail thread and generate a compact content summary. The content summaryis based on relative content contributions provided by the constituentemail messages in the email thread. The content summary may be presentedin a distinct window without disturbing or modifying the email thread orthe email messages. The distinctive content summary disclosed hereincomprises certain sentences that are automatically gleaned from theemail thread, analyzed relative to other sentences in the thread, andpresented in a convenient chronological sequence for user consumption.

Email threads generally represent focused efforts by participantstowards a goal. Every email adds towards the goal or towards consensusbuilding. New emails add value and information to the thread.Conversation starter emails are generally important because they statethe grievance or issue being raised. The most recent email in the threadis also important, because it provides current status and/or directionbeing taken by the email thread, or may even provide the consensus,disposition, or resolution reached. Each email message is centered onnew information, opinion, or findings contributed by the sender, whichinformation may be built upon, ignored, or acknowledged by subsequentemails. To generate a useful thread content summary, the presentinventors devised a number of contributing factors: (i) an email-weightassigned to each email in the email thread, (ii) a word-weight assignedto certain words in each email in the email thread, and (iii) anintersection-score assigned to intersecting sentence pairs selected fromthe emails in the thread. The thread content summary is then composedfrom unique sentences contributed by the highest-scoring sentenceintersections.

The analysis of the email thread comprises assigning an email weight toeach email message in the thread, based on where the respective emailmessage falls in the chronological order of the thread. Generally, emailmessages at the beginning and end of the thread are favored by beingmore heavily weighted on the theory that they provide more usefulinformation about the basis of the thread at the beginning and thetrend, status, or resolution of the thread at the end, as compared tomessages in the middle which may contain digressions and “noise.”

The analysis also comprises assigning a word weight to certain“substantive” words identified in each email message. The word weightmay be a function of how frequently the word appears in the emailmessage and/or in the thread. The word weight also may be a function ofhow frequently the word appeared in an earlier baseline set of emailsand/or whether, in the earlier baseline set of email, the word appearedin emails classified as “important” versus “not-important.” The wordweight may be further biased by the email weight of the email comprisingthe respective word, such that weightier emails will raise a word'sweight. Thus, an initial baseline analysis involves classifying emailmessages as “important” or “not-important” and then word frequency isdetermined for words in the set of important email messages; wordfrequency is separately determined for other words in the email messagesclassified as “not-important.”

The analysis also comprises identifying “intersecting” sentence pairsthat have a set of “intersecting words” in common. Each intersectingsentence pair is scored based on the word weights of the respectiveintersecting words as a function of the weight of the email messagecontaining the sentence in the sentence pair. Thus, intersectingsentence pairs with highly weighted intersecting words (e.g., frequent“important” words) and/or from highly weighted email messages (e.g.,early and late messages) will tend to score higher. On the other hand,intersecting sentence pairs with low word weights (e.g., infrequent“not-important” words) in common and/or from low weighted email messages(e.g., in the middle of the thread) will tend to score lower. Accordingto the illustrative embodiment, a set of unique sentences from thehighest-scoring intersecting sentence pairs are chosen for the contentsummary and are ordered chronologically for presentation to the user.The resulting thread content summary is thus based on relative contentcontributions of individual emails.

The thread content summary is enhanced by hyperlinking each sentencetherein to a number of information sources and/or content. For example,sentences in the thread summary are hyperlinked to the original email,to detailed information about the sender (e.g., name, title,organization, contact information, etc.), and/or to detailed customerinformation referenced in the source email (e.g., customer accountnumber and contact, storage operation cell information, geographiclocation, configuration data, etc.). The thread content summary isfurther enhanced by gleaning deadlines or other operative dates from theemails and presenting a selection of date-times for the user to choosefrom. The user's choice is then entered as a calendar event, thusgreatly facilitating decision-making based on the thread summary.

The email thread analysis is further enhanced by automatically copyingany attachments in the emails to a specially configured “edge drive”that acts as a component of a data storage management system. Edge driveis a data repository allowing data copied to the edge drive to beavailable to the user on that client or other client computers. Forexample, users can configure edge drive on a desktop computer, copyfiles to the edge drive, and those files are then accessible from theirlaptop, and through a web interface. Files in edge drive are protected,so users can retrieve the files from edge drive to another location evenif the original files are lost. Accordingly, the data stored to the edgedrive is automatically protected by data backups (and other storageoperations) governed and managed by the data storage management systemapart from what happens to the emails or the email thread or the threadcontent summary. The attachments are left undisturbed in the originalemails. Optionally, the attachments may be replaced with stubs and/orpointers in the original email messages, pointing to the edge drive orto the secondary storage subsystem where the attachments are backed up.For sensitive data that may be included in such attachments, using theedge drive provides an important additional level of data protection,apart from the email system that handles the emails, thus bringing theattachments within the ambit of the data storage management system andits superior data protection features.

One of the illustrative techniques comprises: identifying, by acomputing device executing an email application, a baseline set of emailmessages received and sent during a predefined baseline period of time;and classifying, by the computing device, each email in the baseline setof emails as either important or not-important; wherein an email messageis more likely to be classified as important rather than not-important,by the computing device, when one or more of: (i) the respective emailmessage was read by a user of the computing device executing the emailapplication, (ii) the user responded to the respective email message,(iii) a follow-up flag was entered for the respective email message, and(iv) the respective email message was addressed individually to theuser.

Another illustrative method comprises: classifying, by a computingdevice executing an email application, a baseline set of email messagesreceived and sent during a predefined baseline period of time, whereineach email message in the baseline set is classified as either importantor not-important; wherein an email message in the baseline set is morelikely to be classified as important rather than not-important, by thecomputing device, when one or more of: (i) the respective email messagewas read by a user of the computing device executing the emailapplication, (ii) the user responded to the respective email message,(iii) a follow-up flag is associated with the respective email message,and (iv) the respective email message was addressed individually to theuser; generating a first word-frequency table comprising words in theemail messages classified as important, wherein each word therein isassociated with a measure of frequency of occurrence of the respectiveword in the email messages classified as important; generating a secondword-frequency table comprising words in the email messages classifiedas not-important, which are not in the first word-frequency table,wherein each word in the second word-frequency table is associated witha measure of frequency of occurrence of the respective word in the emailmessages classified as not-important; generating, by the computingdevice, a content summary of an email-thread comprising a plurality ofemail messages which are distinct from and created after the baselineset of email messages, wherein the content summary is based on one ormore of: (a) the measure of frequency of a given word stored in thefirst word-frequency table or second word-frequency table, and (b)whether the given word is in the first word-frequency table versus inthe second word-frequency table.

An illustrative computer-readable medium, excluding transitorypropagating signals, storing instructions that, when executed by atleast one computing device comprising one or more processors andcomputer-readable memory for storing the instructions, cause thecomputing device to perform operations comprising: executing an emailapplication; classifying a baseline set of email messages received andsent during a predefined baseline period of time, wherein each emailmessage in the baseline set is classified as either important ornot-important; wherein an email message in the baseline set is morelikely to be classified as important rather than not-important, by thecomputing device, when one or more of: (i) the respective email messagewas read by a user of the computing device executing the emailapplication, (ii) the user responded to the respective email message,(iii) a follow-up flag is associated with the respective email message,and (iv) the respective email message was addressed individually to theuser; generating a first word-frequency table comprising words in theemail messages classified as important, wherein each word therein isassociated with a measure of frequency of occurrence of the respectiveword in the email messages classified as important; generating a secondword-frequency table comprising words in the email messages classifiedas not-important, which are not in the first word-frequency table,wherein each word in the second word-frequency table is associated witha measure of frequency of occurrence of the respective word in the emailmessages classified as not-important.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram illustrating an exemplary informationmanagement system.

FIG. 1B is a detailed view of a primary storage device, a secondarystorage device, and some examples of primary data and secondary copydata.

FIG. 1C is a block diagram of an exemplary information management systemincluding a storage manager, one or more data agents, and one or moremedia agents.

FIG. 1D is a block diagram illustrating a scalable informationmanagement system.

FIG. 1E illustrates certain secondary copy operations according to anexemplary storage policy.

FIGS. 1F-1H are block diagrams illustrating suitable data structuresthat may be employed by the information management system.

FIG. 2A illustrates a system and technique for synchronizing primarydata to a destination such as a failover site using secondary copy data.

FIG. 2B illustrates an information management system architectureincorporating use of a network file system (NFS) protocol forcommunicating between the primary and secondary storage subsystems.

FIG. 2C is a block diagram of an example of a highly scalable manageddata pool architecture.

FIG. 3A is a block diagram illustrating some salient portions of astorage management system 300 for summarization and processing of emailon a client computing device, according to an illustrative embodiment ofthe present invention.

FIG. 3B is a block diagram depicting some salient details of a clientcomputing device 302, which is a component of system 300.

FIG. 4 depicts some salient operations of a method 400 according to anillustrative embodiment of the present invention.

FIG. 5 depicts some salient sub-operations of block 404 in method 400.

FIG. 6 depicts some salient sub-operations of block 408 in method 400.

FIG. 7 depicts some salient sub-operations of block 604 in method 400.

FIG. 8 depicts an example screenshot of a user interface showing athread summary according to the illustrative embodiment.

DETAILED DESCRIPTION

Detailed descriptions and examples of systems and methods according toone or more illustrative embodiments of the present invention may befound in the section entitled SUMMARIZATION OF EMAIL ON A CLIENTCOMPUTING DEVICE BASED ON CONTENT CONTRIBUTION TO AN EMAIL THREAD USINGCLASSIFICATION AND WORD FREQUENCY CONSIDERATIONS, as well as in thesection entitled Example Embodiments, and also in FIGS. 3A-8 herein.Furthermore, components and functionality for summarization andprocessing of email on a client computing device based on contentcontribution to an email thread may be configured and/or incorporatedinto information management systems such as those described herein inFIGS. 1A-1H and 2A-2C.

Various embodiments described herein are intimately tied to, enabled by,and would not exist except for, computer technology. For example,training, summarization, and processing of email based on contentcontribution to an email thread as described herein in reference tovarious embodiments cannot reasonably be performed by humans alone,without the computer technology upon which they are implemented.

Information Management System Overview

With the increasing importance of protecting and leveraging data,organizations simply cannot risk losing critical data. Moreover, runawaydata growth and other modern realities make protecting and managing dataincreasingly difficult. There is therefore a need for efficient,powerful, and user-friendly solutions for protecting and managing dataand for smart and efficient management of data storage. Depending on thesize of the organization, there may be many data production sourceswhich are under the purview of tens, hundreds, or even thousands ofindividuals. In the past, individuals were sometimes responsible formanaging and protecting their own data, and a patchwork of hardware andsoftware point solutions may have been used in any given organization.These solutions were often provided by different vendors and had limitedor no interoperability. Certain embodiments described herein addressthese and other shortcomings of prior approaches by implementingscalable, unified, organization-wide information management, includingdata storage management.

FIG. 1A shows one such information management system 100 (or “system100”), which generally includes combinations of hardware and softwareconfigured to protect and manage data and metadata that are generatedand used by computing devices in system 100. System 100 may be referredto in some embodiments as a “storage management system” or a “datastorage management system.” System 100 performs information managementoperations, some of which may be referred to as “storage operations” or“data storage operations,” to protect and manage the data residing inand/or managed by system 100. The organization that employs system 100may be a corporation or other business entity, non-profit organization,educational institution, household, governmental agency, or the like.

Generally, the systems and associated components described herein may becompatible with and/or provide some or all of the functionality of thesystems and corresponding components described in one or more of thefollowing U.S. patents/publications and patent applications assigned toCommvault Systems, Inc., each of which is hereby incorporated byreference in its entirety herein:

-   -   U.S. Pat. No. 7,035,880, entitled “Modular Backup and Retrieval        System Used in Conjunction With a Storage Area Network”;    -   U.S. Pat. No. 7,107,298, entitled “System And Method For        Archiving Objects In An Information Store”;    -   U.S. Pat. No. 7,246,207, entitled “System and Method for        Dynamically Performing Storage Operations in a Computer        Network”;    -   U.S. Pat. No. 7,315,923, entitled “System And Method For        Combining Data Streams In Pipelined Storage Operations In A        Storage Network”;    -   U.S. Pat. No. 7,343,453, entitled “Hierarchical Systems and        Methods for Providing a Unified View of Storage Information”;    -   U.S. Pat. No. 7,395,282, entitled “Hierarchical Backup and        Retrieval System”;    -   U.S. Pat. No. 7,529,782, entitled “System and Methods for        Performing a Snapshot and for Restoring Data”;    -   U.S. Pat. No. 7,617,262, entitled “System and Methods for        Monitoring Application Data in a Data Replication System”;    -   U.S. Pat. No. 7,734,669, entitled “Managing Copies Of Data”;    -   U.S. Pat. No. 7,747,579, entitled “Metabase for Facilitating        Data Classification”;    -   U.S. Pat. No. 8,156,086, entitled “Systems And Methods For        Stored Data Verification”;    -   U.S. Pat. No. 8,170,995, entitled “Method and System for Offline        Indexing of Content and Classifying Stored Data”;    -   U.S. Pat. No. 8,230,195, entitled “System And Method For        Performing Auxiliary Storage Operations”;    -   U.S. Pat. No. 8,285,681, entitled “Data Object Store and Server        for a Cloud Storage Environment, Including Data Deduplication        and Data Management Across Multiple Cloud Storage Sites”;    -   U.S. Pat. No. 8,307,177, entitled “Systems And Methods For        Management Of Virtualization Data”;    -   U.S. Pat. No. 8,364,652, entitled “Content-Aligned, Block-Based        Deduplication”;    -   U.S. Pat. No. 8,578,120, entitled “Block-Level Single        Instancing”;    -   U.S. Pat. No. 8,954,446, entitled “Client-Side Repository in a        Networked Deduplicated Storage System”;    -   U.S. Pat. No. 9,020,900, entitled “Distributed Deduplicated        Storage System”;    -   U.S. Pat. No. 9,098,495, entitled “Application-Aware and Remote        Single Instance Data Management”;    -   U.S. Pat. No. 9,239,687, entitled “Systems and Methods for        Retaining and Using Data Block Signatures in Data Protection        Operations”;    -   U.S. Pat. Pub. No. 2006/0224846, entitled “System and Method to        Support Single Instance Storage Operations”;    -   U.S. Pat. Pub. No. 2014/0201170, entitled “High Availability        Distributed Deduplicated Storage System”;    -   U.S. patent application Ser. No. 14/721,971, entitled        “Replication Using Deduplicated Secondary Copy Data”;    -   U.S. Patent Application No. 62/265,339 entitled “Live        Synchronization and Management of Virtual Machines across        Computing and Virtualization Platforms and Using Live        Synchronization to Support Disaster Recovery”;    -   U.S. Patent Application No. 62/273,286 entitled “Redundant and        Robust Distributed Deduplication Data Storage System”;    -   U.S. Patent Application No. 62/294,920 and Ser. No. 15/283,033,        entitled “Data Protection Operations Based on Network Path        Information”;    -   U.S. Patent Application Nos. 62/297,057 and Ser. No. 15/286,403,        entitled “Data Restoration Operations Based on Network Path        Information”; and    -   U.S. Patent Application No. 62/387,384, entitled        “Application-Level Live Synchronization Across Computing        Platforms Including Synchronizing Co-Resident Applications To        Disparate Standby Destinations And Selectively Synchronizing        Some Applications And Not Others”.

System 100 includes computing devices and computing technologies. Forinstance, system 100 can include one or more client computing devices102 and secondary storage computing devices 106, as well as storagemanager 140 or a host computing device for it. Computing devices caninclude, without limitation, one or more: workstations, personalcomputers, desktop computers, or other types of generally fixedcomputing systems such as mainframe computers, servers, andminicomputers. Other computing devices can include mobile or portablecomputing devices, such as one or more laptops, tablet computers,personal data assistants, mobile phones (such as smartphones), and othermobile or portable computing devices such as embedded computers, set topboxes, vehicle-mounted devices, wearable computers, etc. Servers caninclude mail servers, file servers, database servers, virtual machineservers, and web servers. Any given computing device comprises one ormore processors (e.g., CPU and/or single-core or multi-core processors),as well as corresponding non-transitory computer memory (e.g.,random-access memory (RAM)) for storing computer programs which are tobe executed by the one or more processors. Other computer memory formass storage of data may be packaged/configured with the computingdevice (e.g., an internal hard disk) and/or may be external andaccessible by the computing device (e.g., network-attached storage, astorage array, etc.). In some cases, a computing device includes cloudcomputing resources, which may be implemented as virtual machines. Forinstance, one or more virtual machines may be provided to theorganization by a third-party cloud service vendor.

In some embodiments, computing devices can include one or more virtualmachine(s) running on a physical host computing device (or “hostmachine”) operated by the organization. As one example, the organizationmay use one virtual machine as a database server and another virtualmachine as a mail server, both virtual machines operating on the samehost machine. A Virtual machine (“VM”) is a software implementation of acomputer that does not physically exist and is instead instantiated inan operating system of a physical computer (or host machine) to enableapplications to execute within the VM's environment, i.e., a VM emulatesa physical computer. A VM includes an operating system and associatedvirtual resources, such as computer memory and processor(s). Ahypervisor operates between the VM and the hardware of the physical hostmachine and is generally responsible for creating and running the VMs.Hypervisors are also known in the art as virtual machine monitors or avirtual machine managers or “VMMs”, and may be implemented in software,firmware, and/or specialized hardware installed on the host machine.Examples of hypervisors include ESX Server, by VMware, Inc. of PaloAlto, Calif.; Microsoft Virtual Server and Microsoft Windows ServerHyper-V, both by Microsoft Corporation of Redmond, Wash.; Sun xVM byOracle America Inc. of Santa Clara, Calif.; and Xen by Citrix Systems,Santa Clara, Calif. The hypervisor provides resources to each virtualoperating system such as a virtual processor, virtual memory, a virtualnetwork device, and a virtual disk. Each virtual machine has one or moreassociated virtual disks. The hypervisor typically stores the data ofvirtual disks in files on the file system of the physical host machine,called virtual machine disk files (“VMDK” in VMware lingo) or virtualhard disk image files (in Microsoft lingo). For example, VMware's ESXServer provides the Virtual Machine File System (VMFS) for the storageof virtual machine disk files. A virtual machine reads data from andwrites data to its virtual disk much the way that a physical machinereads data from and writes data to a physical disk. Examples oftechniques for implementing information management in a cloud computingenvironment are described in U.S. Pat. No. 8,285,681. Examples oftechniques for implementing information management in a virtualizedcomputing environment are described in U.S. Pat. No. 8,307,177.

Information management system 100 can also include electronic datastorage devices, generally used for mass storage of data, including,e.g., primary storage devices 104 and secondary storage devices 108.Storage devices can generally be of any suitable type including, withoutlimitation, disk drives, storage arrays (e.g., storage-area network(SAN) and/or network-attached storage (NAS) technology), semiconductormemory (e.g., solid state storage devices), network attached storage(NAS) devices, tape libraries, or other magnetic, non-tape storagedevices, optical media storage devices, DNA/RNA-based memory technology,combinations of the same, etc. In some embodiments, storage devices formpart of a distributed file system. In some cases, storage devices areprovided in a cloud storage environment (e.g., a private cloud or oneoperated by a third-party vendor), whether for primary data or secondarycopies or both.

Depending on context, the term “information management system” can referto generally all of the illustrated hardware and software components inFIG. 1C, or the term may refer to only a subset of the illustratedcomponents. For instance, in some cases, system 100 generally refers toa combination of specialized components used to protect, move, manage,manipulate, analyze, and/or process data and metadata generated byclient computing devices 102. However, system 100 in some cases does notinclude the underlying components that generate and/or store primarydata 112, such as the client computing devices 102 themselves, and theprimary storage devices 104. Likewise secondary storage devices 108(e.g., a third-party provided cloud storage environment) may not be partof system 100. As an example, “information management system” or“storage management system” may sometimes refer to one or more of thefollowing components, which will be described in further detail below:storage manager, data agent, and media agent.

One or more client computing devices 102 may be part of system 100, eachclient computing device 102 having an operating system and at least oneapplication 110 and one or more accompanying data agents executingthereon; and associated with one or more primary storage devices 104storing primary data 112. Client computing device(s) 102 and primarystorage devices 104 may generally be referred to in some cases asprimary storage subsystem 117.

Client Computing Devices, Clients, and Subclients

Typically, a variety of sources in an organization produce data to beprotected and managed. As just one illustrative example, in a corporateenvironment such data sources can be employee workstations and companyservers such as a mail server, a web server, a database server, atransaction server, or the like. In system 100, data generation sourcesinclude one or more client computing devices 102. A computing devicethat has a data agent 142 installed and operating on it is generallyreferred to as a “client computing device” 102, and may include any typeof computing device, without limitation. A client computing device 102may be associated with one or more users and/or user accounts.

A “client” is a logical component of information management system 100,which may represent a logical grouping of one or more data agentsinstalled on a client computing device 102. Storage manager 140recognizes a client as a component of system 100, and in someembodiments, may automatically create a client component the first timea data agent 142 is installed on a client computing device 102. Becausedata generated by executable component(s) 110 is tracked by theassociated data agent 142 so that it may be properly protected in system100, a client may be said to generate data and to store the generateddata to primary storage, such as primary storage device 104. However,the terms “client” and “client computing device” as used herein do notimply that a client computing device 102 is necessarily configured inthe client/server sense relative to another computing device such as amail server, or that a client computing device 102 cannot be a server inits own right. As just a few examples, a client computing device 102 canbe and/or include mail servers, file servers, database servers, virtualmachine servers, and/or web servers.

Each client computing device 102 may have application(s) 110 executingthereon which generate and manipulate the data that is to be protectedfrom loss and managed in system 100. Applications 110 generallyfacilitate the operations of an organization, and can include, withoutlimitation, mail server applications (e.g., Microsoft Exchange Server),file system applications, mail client applications (e.g., MicrosoftExchange Client), database applications or database management systems(e.g., SQL, Oracle, SAP, Lotus Notes Database), word processingapplications (e.g., Microsoft Word), spreadsheet applications, financialapplications, presentation applications, graphics and/or videoapplications, browser applications, mobile applications, entertainmentapplications, and so on. Each application 110 may be accompanied by anapplication-specific data agent 142, though not all data agents 142 areapplication-specific or associated with only application. A file system,e.g., Microsoft Windows Explorer, may be considered an application 110and may be accompanied by its own data agent 142. Client computingdevices 102 can have at least one operating system (e.g., MicrosoftWindows, Mac OS X, iOS, IBM z/OS, Linux, other Unix-based operatingsystems, etc.) installed thereon, which may support or host one or morefile systems and other applications 110. In some embodiments, a virtualmachine that executes on a host client computing device 102 may beconsidered an application 110 and may be accompanied by a specific dataagent 142 (e.g., virtual server data agent).

Client computing devices 102 and other components in system 100 can beconnected to one another via one or more electronic communicationpathways 114. For example, a first communication pathway 114 maycommunicatively couple client computing device 102 and secondary storagecomputing device 106; a second communication pathway 114 maycommunicatively couple storage manager 140 and client computing device102; and a third communication pathway 114 may communicatively couplestorage manager 140 and secondary storage computing device 106, etc.(see, e.g., FIG. 1A and FIG. 1C). A communication pathway 114 caninclude one or more networks or other connection types including one ormore of the following, without limitation: the Internet, a wide areanetwork (WAN), a local area network (LAN), a Storage Area Network (SAN),a Fibre Channel (FC) connection, a Small Computer System Interface(SCSI) connection, a virtual private network (VPN), a token ring orTCP/IP based network, an intranet network, a point-to-point link, acellular network, a wireless data transmission system, a two-way cablesystem, an interactive kiosk network, a satellite network, a broadbandnetwork, a baseband network, a neural network, a mesh network, an ad hocnetwork, other appropriate computer or telecommunications networks,combinations of the same or the like. Communication pathways 114 in somecases may also include application programming interfaces (APIs)including, e.g., cloud service provider APIs, virtual machine managementAPIs, and hosted service provider APIs. The underlying infrastructure ofcommunication pathways 114 may be wired and/or wireless, analog and/ordigital, or any combination thereof; and the facilities used may beprivate, public, third-party provided, or any combination thereof,without limitation.

A “subclient” is a logical grouping of all or part of a client's primarydata 112. In general, a subclient may be defined according to how thesubclient data is to be protected as a unit in system 100. For example,a subclient may be associated with a certain storage policy. A givenclient may thus comprise several subclients, each subclient associatedwith a different storage policy. For example, some files may form afirst subclient that requires compression and deduplication and isassociated with a first storage policy. Other files of the client mayform a second subclient that requires a different retention schedule aswell as encryption, and may be associated with a different, secondstorage policy. As a result, though the primary data may be generated bythe same application 110 and may belong to one given client, portions ofthe data may be assigned to different subclients for distinct treatmentby system 100. More detail on subclients is given in regard to storagepolicies below.

Primary Data and Exemplary Primary Storage Devices

Primary data 112 is generally production data or “live” data generatedby the operating system and/or applications 110 executing on clientcomputing device 102. Primary data 112 is generally stored on primarystorage device(s) 104 and is organized via a file system operating onthe client computing device 102. Thus, client computing device(s) 102and corresponding applications 110 may create, access, modify, write,delete, and otherwise use primary data 112. Primary data 112 isgenerally in the native format of the source application 110. Primarydata 112 is an initial or first stored body of data generated by thesource application 110. Primary data 112 in some cases is createdsubstantially directly from data generated by the corresponding sourceapplication 110. It can be useful in performing certain tasks toorganize primary data 112 into units of different granularities. Ingeneral, primary data 112 can include files, directories, file systemvolumes, data blocks, extents, or any other hierarchies or organizationsof data objects. As used herein, a “data object” can refer to (i) anyfile that is currently addressable by a file system or that waspreviously addressable by the file system (e.g., an archive file),and/or to (ii) a subset of such a file (e.g., a data block, an extent,etc.). Primary data 112 may include structured data (e.g., databasefiles), unstructured data (e.g., documents), and/or semi-structureddata. See, e.g., FIG. 1B.

It can also be useful in performing certain functions of system 100 toaccess and modify metadata within primary data 112. Metadata generallyincludes information about data objects and/or characteristicsassociated with the data objects. For simplicity herein, it is to beunderstood that, unless expressly stated otherwise, any reference toprimary data 112 generally also includes its associated metadata, butreferences to metadata generally do not include the primary data.Metadata can include, without limitation, one or more of the following:the data owner (e.g., the client or user that generates the data), thelast modified time (e.g., the time of the most recent modification ofthe data object), a data object name (e.g., a file name), a data objectsize (e.g., a number of bytes of data), information about the content(e.g., an indication as to the existence of a particular search term),user-supplied tags, to/from information for email (e.g., an emailsender, recipient, etc.), creation date, file type (e.g., format orapplication type), last accessed time, application type (e.g., type ofapplication that generated the data object), location/network (e.g., acurrent, past or future location of the data object and network pathwaysto/from the data object), geographic location (e.g., GPS coordinates),frequency of change (e.g., a period in which the data object ismodified), business unit (e.g., a group or department that generates,manages or is otherwise associated with the data object), aginginformation (e.g., a schedule, such as a time period, in which the dataobject is migrated to secondary or long term storage), boot sectors,partition layouts, file location within a file folder directorystructure, user permissions, owners, groups, access control lists(ACLs), system metadata (e.g., registry information), combinations ofthe same or other similar information related to the data object. Inaddition to metadata generated by or related to file systems andoperating systems, some applications 110 and/or other components ofsystem 100 maintain indices of metadata for data objects, e.g., metadataassociated with individual email messages. The use of metadata toperform classification and other functions is described in greaterdetail below.

Primary storage devices 104 storing primary data 112 may be relativelyfast and/or expensive technology (e.g., flash storage, a disk drive, ahard-disk storage array, solid state memory, etc.), typically to supporthigh-performance live production environments. Primary data 112 may behighly changeable and/or may be intended for relatively short termretention (e.g., hours, days, or weeks). According to some embodiments,client computing device 102 can access primary data 112 stored inprimary storage device 104 by making conventional file system calls viathe operating system. Each client computing device 102 is generallyassociated with and/or in communication with one or more primary storagedevices 104 storing corresponding primary data 112. A client computingdevice 102 is said to be associated with or in communication with aparticular primary storage device 104 if it is capable of one or moreof: routing and/or storing data (e.g., primary data 112) to the primarystorage device 104, coordinating the routing and/or storing of data tothe primary storage device 104, retrieving data from the primary storagedevice 104, coordinating the retrieval of data from the primary storagedevice 104, and modifying and/or deleting data in the primary storagedevice 104. Thus, a client computing device 102 may be said to accessdata stored in an associated storage device 104.

Primary storage device 104 may be dedicated or shared. In some cases,each primary storage device 104 is dedicated to an associated clientcomputing device 102, e.g., a local disk drive. In other cases, one ormore primary storage devices 104 can be shared by multiple clientcomputing devices 102, e.g., via a local network, in a cloud storageimplementation, etc. As one example, primary storage device 104 can be astorage array shared by a group of client computing devices 102, such asEMC Clariion, EMC Symmetrix, EMC Celerra, Dell EqualLogic, IBM XIV,NetApp FAS, HP EVA, and HP 3PAR.

System 100 may also include hosted services (not shown), which may behosted in some cases by an entity other than the organization thatemploys the other components of system 100. For instance, the hostedservices may be provided by online service providers. Such serviceproviders can provide social networking services, hosted email services,or hosted productivity applications or other hosted applications such assoftware-as-a-service (SaaS), platform-as-a-service (PaaS), applicationservice providers (ASPS), cloud services, or other mechanisms fordelivering functionality via a network. As it services users, eachhosted service may generate additional data and metadata, which may bemanaged by system 100, e.g., as primary data 112. In some cases, thehosted services may be accessed using one of the applications 110. As anexample, a hosted mail service may be accessed via browser running on aclient computing device 102.

Secondary Copies and Exemplary Secondary Storage Devices

Primary data 112 stored on primary storage devices 104 may becompromised in some cases, such as when an employee deliberately oraccidentally deletes or overwrites primary data 112. Or primary storagedevices 104 can be damaged, lost, or otherwise corrupted. For recoveryand/or regulatory compliance purposes, it is therefore useful togenerate and maintain copies of primary data 112. Accordingly, system100 includes one or more secondary storage computing devices 106 and oneor more secondary storage devices 108 configured to create and store oneor more secondary copies 116 of primary data 112 including itsassociated metadata. The secondary storage computing devices 106 and thesecondary storage devices 108 may be referred to as secondary storagesubsystem 118.

Secondary copies 116 can help in search and analysis efforts and meetother information management goals as well, such as: restoring dataand/or metadata if an original version is lost (e.g., by deletion,corruption, or disaster); allowing point-in-time recovery; complyingwith regulatory data retention and electronic discovery (e-discovery)requirements; reducing utilized storage capacity in the productionsystem and/or in secondary storage; facilitating organization and searchof data; improving user access to data files across multiple computingdevices and/or hosted services; and implementing data retention andpruning policies.

A secondary copy 116 can comprise a separate stored copy of data that isderived from one or more earlier-created stored copies (e.g., derivedfrom primary data 112 or from another secondary copy 116). Secondarycopies 116 can include point-in-time data, and may be intended forrelatively long-term retention before some or all of the data is movedto other storage or discarded. In some cases, a secondary copy 116 maybe in a different storage device than other previously stored copies;and/or may be remote from other previously stored copies. Secondarycopies 116 can be stored in the same storage device as primary data 112.For example, a disk array capable of performing hardware snapshotsstores primary data 112 and creates and stores hardware snapshots of theprimary data 112 as secondary copies 116. Secondary copies 116 may bestored in relatively slow and/or lower cost storage (e.g., magnetictape). A secondary copy 116 may be stored in a backup or archive format,or in some other format different from the native source applicationformat or other format of primary data 112.

Secondary storage computing devices 106 may index secondary copies 116(e.g., using a media agent 144), enabling users to browse and restore ata later time and further enabling the lifecycle management of theindexed data. After creation of a secondary copy 116 that representscertain primary data 112, a pointer or other location indicia (e.g., astub) may be placed in primary data 112, or be otherwise associated withprimary data 112, to indicate the current location of a particularsecondary copy 116. Since an instance of a data object or metadata inprimary data 112 may change over time as it is modified by application110 (or hosted service or the operating system), system 100 may createand manage multiple secondary copies 116 of a particular data object ormetadata, each copy representing the state of the data object in primarydata 112 at a particular point in time. Moreover, since an instance of adata object in primary data 112 may eventually be deleted from primarystorage device 104 and the file system, system 100 may continue tomanage point-in-time representations of that data object, even thoughthe instance in primary data 112 no longer exists. For virtual machines,the operating system and other applications 110 of client computingdevice(s) 102 may execute within or under the management ofvirtualization software (e.g., a VMM), and the primary storage device(s)104 may comprise a virtual disk created on a physical storage device.System 100 may create secondary copies 116 of the files or other dataobjects in a virtual disk file and/or secondary copies 116 of the entirevirtual disk file itself (e.g., of an entire .vmdk file).

Secondary copies 116 are distinguishable from corresponding primary data112. First, secondary copies 116 can be stored in a different formatfrom primary data 112 (e.g., backup, archive, or other non-nativeformat). For this or other reasons, secondary copies 116 may not bedirectly usable by applications 110 or client computing device 102(e.g., via standard system calls or otherwise) without modification,processing, or other intervention by system 100 which may be referred toas “restore” operations. Secondary copies 116 may have been processed bydata agent 142 and/or media agent 144 in the course of being created(e.g., compression, deduplication, encryption, integrity markers,indexing, formatting, application-aware metadata, etc.), and thussecondary copy 116 may represent source primary data 112 withoutnecessarily being exactly identical to the source.

Second, secondary copies 116 may be stored on a secondary storage device108 that is inaccessible to application 110 running on client computingdevice 102 and/or hosted service. Some secondary copies 116 may be“offline copies,” in that they are not readily available (e.g., notmounted to tape or disk). Offline copies can include copies of data thatsystem 100 can access without human intervention (e.g., tapes within anautomated tape library, but not yet mounted in a drive), and copies thatthe system 100 can access only with some human intervention (e.g., tapeslocated at an offsite storage site).

Using Intermediate Devices for Creating Secondary Copies—SecondaryStorage Computing Devices

Creating secondary copies can be challenging when hundreds or thousandsof client computing devices 102 continually generate large volumes ofprimary data 112 to be protected. Also, there can be significantoverhead involved in the creation of secondary copies 116. Moreover,specialized programmed intelligence and/or hardware capability isgenerally needed for accessing and interacting with secondary storagedevices 108. Client computing devices 102 may interact directly with asecondary storage device 108 to create secondary copies 116, but in viewof the factors described above, this approach can negatively impact theability of client computing device 102 to serve/service application 110and produce primary data 112. Further, any given client computing device102 may not be optimized for interaction with certain secondary storagedevices 108.

Thus, system 100 may include one or more software and/or hardwarecomponents which generally act as intermediaries between clientcomputing devices 102 (that generate primary data 112) and secondarystorage devices 108 (that store secondary copies 116). In addition tooff-loading certain responsibilities from client computing devices 102,these intermediate components provide other benefits. For instance, asdiscussed further below with respect to FIG. 1D, distributing some ofthe work involved in creating secondary copies 116 can enhancescalability and improve system performance. For instance, usingspecialized secondary storage computing devices 106 and media agents 144for interfacing with secondary storage devices 108 and/or for performingcertain data processing operations can greatly improve the speed withwhich system 100 performs information management operations and can alsoimprove the capacity of the system to handle large numbers of suchoperations, while reducing the computational load on the productionenvironment of client computing devices 102. The intermediate componentscan include one or more secondary storage computing devices 106 as shownin FIG. 1A and/or one or more media agents 144. Media agents arediscussed further below (e.g., with respect to FIGS. 1C-1E). Thesespecial-purpose components of system 100 comprise specialized programmedintelligence and/or hardware capability for writing to, reading from,instructing, communicating with, or otherwise interacting with secondarystorage devices 108.

Secondary storage computing device(s) 106 can comprise any of thecomputing devices described above, without limitation. In some cases,secondary storage computing device(s) 106 also include specializedhardware componentry and/or software intelligence (e.g., specializedinterfaces) for interacting with certain secondary storage device(s) 108with which they may be specially associated.

To create a secondary copy 116 involving the copying of data fromprimary storage subsystem 117 to secondary storage subsystem 118, clientcomputing device 102 may communicate the primary data 112 to be copied(or a processed version thereof generated by a data agent 142) to thedesignated secondary storage computing device 106, via a communicationpathway 114. Secondary storage computing device 106 in turn may furtherprocess and convey the data or a processed version thereof to secondarystorage device 108. One or more secondary copies 116 may be created fromexisting secondary copies 116, such as in the case of an auxiliary copyoperation, described further below.

Exemplary Primary Data and an Exemplary Secondary Copy

FIG. 1B is a detailed view of some specific examples of primary datastored on primary storage device(s) 104 and secondary copy data storedon secondary storage device(s) 108, with other components of the systemremoved for the purposes of illustration. Stored on primary storagedevice(s) 104 are primary data 112 objects including word processingdocuments 119A-B, spreadsheets 120, presentation documents 122, videofiles 124, image files 126, email mailboxes 128 (and corresponding emailmessages 129A-C), HTML/XML or other types of markup language files 130,databases 132 and corresponding tables or other data structures133A-133C. Some or all primary data 112 objects are associated withcorresponding metadata (e.g., “Meta1-11”), which may include file systemmetadata and/or application-specific metadata. Stored on the secondarystorage device(s) 108 are secondary copy 116 data objects 134A-C whichmay include copies of or may otherwise represent corresponding primarydata 112.

Secondary copy data objects 134A-C can individually represent more thanone primary data object. For example, secondary copy data object 134Arepresents three separate primary data objects 133C, 122, and 129C(represented as 133C′, 122′, and 129C′, respectively, and accompanied bycorresponding metadata Meta11, Meta3, and Meta8, respectively).Moreover, as indicated by the prime mark (′), secondary storagecomputing devices 106 or other components in secondary storage subsystem118 may process the data received from primary storage subsystem 117 andstore a secondary copy including a transformed and/or supplementedrepresentation of a primary data object and/or metadata that isdifferent from the original format, e.g., in a compressed, encrypted,deduplicated, or other modified format. For instance, secondary storagecomputing devices 106 can generate new metadata or other informationbased on said processing, and store the newly generated informationalong with the secondary copies. Secondary copy data object 1348represents primary data objects 120, 1338, and 119A as 120′, 133B′, and119A′, respectively, accompanied by corresponding metadata Meta2,Meta10, and Meta1, respectively. Also, secondary copy data object 134Crepresents primary data objects 133A, 1198, and 129A as 133A′, 119B′,and 129A′, respectively, accompanied by corresponding metadata Meta9,Meta5, and Meta6, respectively.

Exemplary Information Management System Architecture

System 100 can incorporate a variety of different hardware and softwarecomponents, which can in turn be organized with respect to one anotherin many different configurations, depending on the embodiment. There arecritical design choices involved in specifying the functionalresponsibilities of the components and the role of each component insystem 100. Such design choices can impact how system 100 performs andadapts to data growth and other changing circumstances. FIG. 1C shows asystem 100 designed according to these considerations and includes:storage manager 140, one or more data agents 142 executing on clientcomputing device(s) 102 and configured to process primary data 112, andone or more media agents 144 executing on one or more secondary storagecomputing devices 106 for performing tasks involving secondary storagedevices 108.

Storage Manager

Storage manager 140 is a centralized storage and/or information managerthat is configured to perform certain control functions and also tostore certain critical information about system 100—hence storagemanager 140 is said to manage system 100. As noted, the number ofcomponents in system 100 and the amount of data under management can belarge. Managing the components and data is therefore a significant task,which can grow unpredictably as the number of components and data scaleto meet the needs of the organization. For these and other reasons,according to certain embodiments, responsibility for controlling system100, or at least a significant portion of that responsibility, isallocated to storage manager 140. Storage manager 140 can be adaptedindependently according to changing circumstances, without having toreplace or re-design the remainder of the system. Moreover, a computingdevice for hosting and/or operating as storage manager 140 can beselected to best suit the functions and networking needs of storagemanager 140. These and other advantages are described in further detailbelow and with respect to FIG. 1D.

Storage manager 140 may be a software module or other application hostedby a suitable computing device. In some embodiments, storage manager 140is itself a computing device that performs the functions describedherein. Storage manager 140 comprises or operates in conjunction withone or more associated data structures such as a dedicated database(e.g., management database 146), depending on the configuration. Thestorage manager 140 generally initiates, performs, coordinates, and/orcontrols storage and other information management operations performedby system 100, e.g., to protect and control primary data 112 andsecondary copies 116. In general, storage manager 140 is said to managesystem 100, which includes communicating with, instructing, andcontrolling in some circumstances components such as data agents 142 andmedia agents 144, etc.

As shown by the dashed arrowed lines 114 in FIG. 1C, storage manager 140may communicate with, instruct, and/or control some or all elements ofsystem 100, such as data agents 142 and media agents 144. In thismanner, storage manager 140 manages the operation of various hardwareand software components in system 100. In certain embodiments, controlinformation originates from storage manager 140 and status as well asindex reporting is transmitted to storage manager 140 by the managedcomponents, whereas payload data and metadata are generally communicatedbetween data agents 142 and media agents 144 (or otherwise betweenclient computing device(s) 102 and secondary storage computing device(s)106), e.g., at the direction of and under the management of storagemanager 140. Control information can generally include parameters andinstructions for carrying out information management operations, suchas, without limitation, instructions to perform a task associated withan operation, timing information specifying when to initiate a task,data path information specifying what components to communicate with oraccess in carrying out an operation, and the like. In other embodiments,some information management operations are controlled or initiated byother components of system 100 (e.g., by media agents 144 or data agents142), instead of or in combination with storage manager 140.

According to certain embodiments, storage manager 140 provides one ormore of the following functions:

-   -   communicating with data agents 142 and media agents 144,        including transmitting instructions, messages, and/or queries,        as well as receiving status reports, index information,        messages, and/or queries, and responding to same;    -   initiating execution of information management operations;    -   initiating restore and recovery operations;    -   managing secondary storage devices 108 and inventory/capacity of        the same;    -   allocating secondary storage devices 108 for secondary copy        operations;    -   reporting, searching, and/or classification of data in system        100;    -   monitoring completion of and status reporting related to        information management operations and jobs;    -   tracking movement of data within system 100;    -   tracking age information relating to secondary copies 116,        secondary storage devices 108, comparing the age information        against retention guidelines, and initiating data pruning when        appropriate;    -   tracking logical associations between components in system 100;    -   protecting metadata associated with system 100, e.g., in        management database 146;    -   implementing job management, schedule management, event        management, alert management, reporting, job history        maintenance, user security management, disaster recovery        management, and/or user interfacing for system administrators        and/or end users of system 100;    -   sending, searching, and/or viewing of log files; and    -   implementing operations management functionality.

Storage manager 140 may maintain an associated database 146 (or “storagemanager database 146” or “management database 146”) ofmanagement-related data and information management policies 148.Database 146 is stored in computer memory accessible by storage manager140. Database 146 may include a management index 150 (or “index 150”) orother data structure(s) that may store: logical associations betweencomponents of the system; user preferences and/or profiles (e.g.,preferences regarding encryption, compression, or deduplication ofprimary data or secondary copies; preferences regarding the scheduling,type, or other aspects of secondary copy or other operations; mappingsof particular information management users or user accounts to certaincomputing devices or other components, etc.; management tasks; mediacontainerization; other useful data; and/or any combination thereof. Forexample, storage manager 140 may use index 150 to track logicalassociations between media agents 144 and secondary storage devices 108and/or movement of data to/from secondary storage devices 108. Forinstance, index 150 may store data associating a client computing device102 with a particular media agent 144 and/or secondary storage device108, as specified in an information management policy 148.

Administrators and others may configure and initiate certain informationmanagement operations on an individual basis. But while this may beacceptable for some recovery operations or other infrequent tasks, it isoften not workable for implementing on-going organization-wide dataprotection and management. Thus, system 100 may utilize informationmanagement policies 148 for specifying and executing informationmanagement operations on an automated basis. Generally, an informationmanagement policy 148 can include a stored data structure or otherinformation source that specifies parameters (e.g., criteria and rules)associated with storage management or other information managementoperations. Storage manager 140 can process an information managementpolicy 148 and/or index 150 and, based on the results, identify aninformation management operation to perform, identify the appropriatecomponents in system 100 to be involved in the operation (e.g., clientcomputing devices 102 and corresponding data agents 142, secondarystorage computing devices 106 and corresponding media agents 144, etc.),establish connections to those components and/or between thosecomponents, and/or instruct and control those components to carry outthe operation. In this manner, system 100 can translate storedinformation into coordinated activity among the various computingdevices in system 100.

Management database 146 may maintain information management policies 148and associated data, although information management policies 148 can bestored in computer memory at any appropriate location outside managementdatabase 146. For instance, an information management policy 148 such asa storage policy may be stored as metadata in a media agent database 152or in a secondary storage device 108 (e.g., as an archive copy) for usein restore or other information management operations, depending on theembodiment. Information management policies 148 are described furtherbelow. According to certain embodiments, management database 146comprises a relational database (e.g., an SQL database) for trackingmetadata, such as metadata associated with secondary copy operations(e.g., what client computing devices 102 and corresponding subclientdata were protected and where the secondary copies are stored and whichmedia agent 144 performed the storage operation(s)). This and othermetadata may additionally be stored in other locations, such as atsecondary storage computing device 106 or on the secondary storagedevice 108, allowing data recovery without the use of storage manager140 in some cases. Thus, management database 146 may comprise dataneeded to kick off secondary copy operations (e.g., storage policies,schedule policies, etc.), status and reporting information aboutcompleted jobs (e.g., status and error reports on yesterday's backupjobs), and additional information sufficient to enable restore anddisaster recovery operations (e.g., media agent associations, locationindexing, content indexing, etc.).

Storage manager 140 may include a jobs agent 156, a user interface 158,and a management agent 154, all of which may be implemented asinterconnected software modules or application programs. These aredescribed further below.

Jobs agent 156 in some embodiments initiates, controls, and/or monitorsthe status of some or all information management operations previouslyperformed, currently being performed, or scheduled to be performed bysystem 100. A job is a logical grouping of information managementoperations such as daily storage operations scheduled for a certain setof subclients (e.g., generating incremental block-level backup copies116 at a certain time every day for database files in a certaingeographical location). Thus, jobs agent 156 may access informationmanagement policies 148 (e.g., in management database 146) to determinewhen, where, and how to initiate/control jobs in system 100.

Storage Manager User Interfaces

User interface 158 may include information processing and displaysoftware, such as a graphical user interface (GUI), an applicationprogram interface (API), and/or other interactive interface(s) throughwhich users and system processes can retrieve information about thestatus of information management operations or issue instructions tostorage manager 140 and other components. Via user interface 158, usersmay issue instructions to the components in system 100 regardingperformance of secondary copy and recovery operations. For example, auser may modify a schedule concerning the number of pending secondarycopy operations. As another example, a user may employ the GUI to viewthe status of pending secondary copy jobs or to monitor the status ofcertain components in system 100 (e.g., the amount of capacity left in astorage device). Storage manager 140 may track information that permitsit to select, designate, or otherwise identify content indices,deduplication databases, or similar databases or resources or data setswithin its information management cell (or another cell) to be searchedin response to certain queries. Such queries may be entered by the userby interacting with user interface 158.

Various embodiments of information management system 100 may beconfigured and/or designed to generate user interface data usable forrendering the various interactive user interfaces described. The userinterface data may be used by system 100 and/or by another system,device, and/or software program (for example, a browser program), torender the interactive user interfaces. The interactive user interfacesmay be displayed on, for example, electronic displays (including, forexample, touch-enabled displays), consoles, etc., whetherdirect-connected to storage manager 140 or communicatively coupledremotely, e.g., via an internet connection. The present disclosuredescribes various embodiments of interactive and dynamic userinterfaces, some of which may be generated by user interface agent 158,and which are the result of significant technological development. Theuser interfaces described herein may provide improved human-computerinteractions, allowing for significant cognitive and ergonomicefficiencies and advantages over previous systems, including reducedmental workloads, improved decision-making, and the like. User interface158 may operate in a single integrated view or console (not shown). Theconsole may support a reporting capability for generating a variety ofreports, which may be tailored to a particular aspect of informationmanagement.

User interfaces are not exclusive to storage manager 140 and in someembodiments a user may access information locally from a computingdevice component of system 100. For example, some information pertainingto installed data agents 142 and associated data streams may beavailable from client computing device 102. Likewise, some informationpertaining to media agents 144 and associated data streams may beavailable from secondary storage computing device 106.

Storage Manager Management Agent

Management agent 154 can provide storage manager 140 with the ability tocommunicate with other components within system 100 and/or with otherinformation management cells via network protocols and applicationprogramming interfaces (APIs) including, e.g., HTTP, HTTPS, FTP, REST,virtualization software APIs, cloud service provider APIs, and hostedservice provider APIs, without limitation. Management agent 154 alsoallows multiple information management cells to communicate with oneanother. For example, system 100 in some cases may be one informationmanagement cell in a network of multiple cells adjacent to one anotheror otherwise logically related, e.g., in a WAN or LAN. With thisarrangement, the cells may communicate with one another throughrespective management agents 154. Inter-cell communications andhierarchy is described in greater detail in e.g., U.S. Pat. No.7,343,453.

Information Management Cell

An “information management cell” (or “storage operation cell” or “cell”)may generally include a logical and/or physical grouping of acombination of hardware and software components associated withperforming information management operations on electronic data,typically one storage manager 140 and at least one data agent 142(executing on a client computing device 102) and at least one mediaagent 144 (executing on a secondary storage computing device 106). Forinstance, the components shown in FIG. 1C may together form aninformation management cell. Thus, in some configurations, a system 100may be referred to as an information management cell or a storageoperation cell. A given cell may be identified by the identity of itsstorage manager 140, which is generally responsible for managing thecell.

Multiple cells may be organized hierarchically, so that cells mayinherit properties from hierarchically superior cells or be controlledby other cells in the hierarchy (automatically or otherwise).Alternatively, in some embodiments, cells may inherit or otherwise beassociated with information management policies, preferences,information management operational parameters, or other properties orcharacteristics according to their relative position in a hierarchy ofcells. Cells may also be organized hierarchically according to function,geography, architectural considerations, or other factors useful ordesirable in performing information management operations. For example,a first cell may represent a geographic segment of an enterprise, suchas a Chicago office, and a second cell may represent a differentgeographic segment, such as a New York City office. Other cells mayrepresent departments within a particular office, e.g., human resources,finance, engineering, etc. Where delineated by function, a first cellmay perform one or more first types of information management operations(e.g., one or more first types of secondary copies at a certainfrequency), and a second cell may perform one or more second types ofinformation management operations (e.g., one or more second types ofsecondary copies at a different frequency and under different retentionrules). In general, the hierarchical information is maintained by one ormore storage managers 140 that manage the respective cells (e.g., incorresponding management database(s) 146).

Data Agents

A variety of different applications 110 can operate on a given clientcomputing device 102, including operating systems, file systems,database applications, e-mail applications, and virtual machines, justto name a few. And, as part of the process of creating and restoringsecondary copies 116, the client computing device 102 may be tasked withprocessing and preparing the primary data 112 generated by these variousapplications 110. Moreover, the nature of the processing/preparation candiffer across application types, e.g., due to inherent structural,state, and formatting differences among applications 110 and/or theoperating system of client computing device 102. Each data agent 142 istherefore advantageously configured in some embodiments to assist in theperformance of information management operations based on the type ofdata that is being protected at a client-specific and/orapplication-specific level.

Data agent 142 is a component of information system 100 and is generallydirected by storage manager 140 to participate in creating or restoringsecondary copies 116. Data agent 142 may be a software program (e.g., inthe form of a set of executable binary files) that executes on the sameclient computing device 102 as the associated application 110 that dataagent 142 is configured to protect. Data agent 142 is generallyresponsible for managing, initiating, or otherwise assisting in theperformance of information management operations in reference to itsassociated application(s) 110 and corresponding primary data 112 whichis generated/accessed by the particular application(s) 110. Forinstance, data agent 142 may take part in copying, archiving, migrating,and/or replicating of certain primary data 112 stored in the primarystorage device(s) 104. Data agent 142 may receive control informationfrom storage manager 140, such as commands to transfer copies of dataobjects and/or metadata to one or more media agents 144. Data agent 142also may compress, deduplicate, and encrypt certain primary data 112, aswell as capture application-related metadata before transmitting theprocessed data to media agent 144. Data agent 142 also may receiveinstructions from storage manager 140 to restore (or assist inrestoring) a secondary copy 116 from secondary storage device 108 toprimary storage 104, such that the restored data may be properlyaccessed by application 110 in a suitable format as though it wereprimary data 112.

Each data agent 142 may be specialized for a particular application 110.For instance, different individual data agents 142 may be designed tohandle Microsoft Exchange data, Lotus Notes data, Microsoft Windows filesystem data, Microsoft Active Directory Objects data, SQL Server data,SharePoint data, Oracle database data, SAP database data, virtualmachines and/or associated data, and other types of data. A file systemdata agent, for example, may handle data files and/or other file systeminformation. If a client computing device 102 has two or more types ofdata 112, a specialized data agent 142 may be used for each data type.For example, to backup, migrate, and/or restore all of the data on aMicrosoft Exchange server, the client computing device 102 may use: (1)a Microsoft Exchange Mailbox data agent 142 to back up the Exchangemailboxes; (2) a Microsoft Exchange Database data agent 142 to back upthe Exchange databases; (3) a Microsoft Exchange Public Folder dataagent 142 to back up the Exchange Public Folders; and (4) a MicrosoftWindows File System data agent 142 to back up the file system of clientcomputing device 102. In this example, these specialized data agents 142are treated as four separate data agents 142 even though they operate onthe same client computing device 102. Other examples may include archivemanagement data agents such as a migration archiver or a compliancearchiver, Quick Recovery® agents, and continuous data replicationagents. Application-specific data agents 142 can provide improvedperformance as compared to generic agents. For instance, becauseapplication-specific data agents 142 may only handle data for a singlesoftware application, the design, operation, and performance of the dataagent 142 can be streamlined. The data agent 142 may therefore executefaster and consume less persistent storage and/or operating memory thandata agents designed to generically accommodate multiple differentsoftware applications 110.

Each data agent 142 may be configured to access data and/or metadatastored in the primary storage device(s) 104 associated with data agent142 and its host client computing device 102, and process the dataappropriately. For example, during a secondary copy operation, dataagent 142 may arrange or assemble the data and metadata into one or morefiles having a certain format (e.g., a particular backup or archiveformat) before transferring the file(s) to a media agent 144 or othercomponent. The file(s) may include a list of files or other metadata. Insome embodiments, a data agent 142 may be distributed between clientcomputing device 102 and storage manager 140 (and any other intermediatecomponents) or may be deployed from a remote location or its functionsapproximated by a remote process that performs some or all of thefunctions of data agent 142. In addition, a data agent 142 may performsome functions provided by media agent 144. Other embodiments may employone or more generic data agents 142 that can handle and process datafrom two or more different applications 110, or that can handle andprocess multiple data types, instead of or in addition to usingspecialized data agents 142. For example, one generic data agent 142 maybe used to back up, migrate and restore Microsoft Exchange Mailbox dataand Microsoft Exchange Database data, while another generic data agentmay handle Microsoft Exchange Public Folder data and Microsoft WindowsFile System data.

Media Agents

As noted, off-loading certain responsibilities from client computingdevices 102 to intermediate components such as secondary storagecomputing device(s) 106 and corresponding media agent(s) 144 can providea number of benefits including improved performance of client computingdevice 102, faster and more reliable information management operations,and enhanced scalability. In one example which will be discussed furtherbelow, media agent 144 can act as a local cache of recently-copied dataand/or metadata stored to secondary storage device(s) 108, thusimproving restore capabilities and performance for the cached data.

Media agent 144 is a component of system 100 and is generally directedby storage manager 140 in creating and restoring secondary copies 116.Whereas storage manager 140 generally manages system 100 as a whole,media agent 144 provides a portal to certain secondary storage devices108, such as by having specialized features for communicating with andaccessing certain associated secondary storage device 108. Media agent144 may be a software program (e.g., in the form of a set of executablebinary files) that executes on a secondary storage computing device 106.Media agent 144 generally manages, coordinates, and facilitates thetransmission of data between a data agent 142 (executing on clientcomputing device 102) and secondary storage device(s) 108 associatedwith media agent 144. For instance, other components in the system mayinteract with media agent 144 to gain access to data stored onassociated secondary storage device(s) 108, (e.g., to browse, read,write, modify, delete, or restore data). Moreover, media agents 144 cangenerate and store information relating to characteristics of the storeddata and/or metadata, or can generate and store other types ofinformation that generally provides insight into the contents of thesecondary storage devices 108—generally referred to as indexing of thestored secondary copies 116. Each media agent 144 may operate on adedicated secondary storage computing device 106, while in otherembodiments a plurality of media agents 144 may operate on the samesecondary storage computing device 106.

A media agent 144 may be associated with a particular secondary storagedevice 108 if that media agent 144 is capable of one or more of: routingand/or storing data to the particular secondary storage device 108;coordinating the routing and/or storing of data to the particularsecondary storage device 108; retrieving data from the particularsecondary storage device 108; coordinating the retrieval of data fromthe particular secondary storage device 108; and modifying and/ordeleting data retrieved from the particular secondary storage device108. Media agent 144 in certain embodiments is physically separate fromthe associated secondary storage device 108. For instance, a media agent144 may operate on a secondary storage computing device 106 in adistinct housing, package, and/or location from the associated secondarystorage device 108. In one example, a media agent 144 operates on afirst server computer and is in communication with a secondary storagedevice(s) 108 operating in a separate rack-mounted RAID-based system.

A media agent 144 associated with a particular secondary storage device108 may instruct secondary storage device 108 to perform an informationmanagement task. For instance, a media agent 144 may instruct a tapelibrary to use a robotic arm or other retrieval means to load or eject acertain storage media, and to subsequently archive, migrate, or retrievedata to or from that media, e.g., for the purpose of restoring data to aclient computing device 102. As another example, a secondary storagedevice 108 may include an array of hard disk drives or solid statedrives organized in a RAID configuration, and media agent 144 mayforward a logical unit number (LUN) and other appropriate information tothe array, which uses the received information to execute the desiredsecondary copy operation. Media agent 144 may communicate with asecondary storage device 108 via a suitable communications link, such asa SCSI or Fibre Channel link.

Each media agent 144 may maintain an associated media agent database152. Media agent database 152 may be stored to a disk or other storagedevice (not shown) that is local to the secondary storage computingdevice 106 on which media agent 144 executes. In other cases, mediaagent database 152 is stored separately from the host secondary storagecomputing device 106. Media agent database 152 can include, among otherthings, a media agent index 153 (see, e.g., FIG. 1C). In some cases,media agent index 153 does not form a part of and is instead separatefrom media agent database 152.

Media agent index 153 (or “index 153”) may be a data structureassociated with the particular media agent 144 that includes informationabout the stored data associated with the particular media agent andwhich may be generated in the course of performing a secondary copyoperation or a restore. Index 153 provides a fast and efficientmechanism for locating/browsing secondary copies 116 or other datastored in secondary storage devices 108 without having to accesssecondary storage device 108 to retrieve the information from there. Forinstance, for each secondary copy 116, index 153 may include metadatasuch as a list of the data objects (e.g., files/subdirectories, databaseobjects, mailbox objects, etc.), a logical path to the secondary copy116 on the corresponding secondary storage device 108, locationinformation (e.g., offsets) indicating where the data objects are storedin the secondary storage device 108, when the data objects were createdor modified, etc. Thus, index 153 includes metadata associated with thesecondary copies 116 that is readily available for use from media agent144. In some embodiments, some or all of the information in index 153may instead or additionally be stored along with secondary copies 116 insecondary storage device 108. In some embodiments, a secondary storagedevice 108 can include sufficient information to enable a “bare metalrestore,” where the operating system and/or software applications of afailed client computing device 102 or another target may beautomatically restored without manually reinstalling individual softwarepackages (including operating systems).

Because index 153 may operate as a cache, it can also be referred to asan “index cache.” In such cases, information stored in index cache 153typically comprises data that reflects certain particulars aboutrelatively recent secondary copy operations. After some triggeringevent, such as after some time elapses or index cache 153 reaches aparticular size, certain portions of index cache 153 may be copied ormigrated to secondary storage device 108, e.g., on a least-recently-usedbasis. This information may be retrieved and uploaded back into indexcache 153 or otherwise restored to media agent 144 to facilitateretrieval of data from the secondary storage device(s) 108. In someembodiments, the cached information may include format orcontainerization information related to archives or other files storedon storage device(s) 108.

In some alternative embodiments media agent 144 generally acts as acoordinator or facilitator of secondary copy operations between clientcomputing devices 102 and secondary storage devices 108, but does notactually write the data to secondary storage device 108. For instance,storage manager 140 (or media agent 144) may instruct a client computingdevice 102 and secondary storage device 108 to communicate with oneanother directly. In such a case, client computing device 102 transmitsdata directly or via one or more intermediary components to secondarystorage device 108 according to the received instructions, and viceversa. Media agent 144 may still receive, process, and/or maintainmetadata related to the secondary copy operations, i.e., may continue tobuild and maintain index 153. In these embodiments, payload data canflow through media agent 144 for the purposes of populating index 153,but not for writing to secondary storage device 108. Media agent 144and/or other components such as storage manager 140 may in some casesincorporate additional functionality, such as data classification,content indexing, deduplication, encryption, compression, and the like.Further details regarding these and other functions are described below.

Distributed, Scalable Architecture

As described, certain functions of system 100 can be distributed amongstvarious physical and/or logical components. For instance, one or more ofstorage manager 140, data agents 142, and media agents 144 may operateon computing devices that are physically separate from one another. Thisarchitecture can provide a number of benefits. For instance, hardwareand software design choices for each distributed component can betargeted to suit its particular function. The secondary computingdevices 106 on which media agents 144 operate can be tailored forinteraction with associated secondary storage devices 108 and providefast index cache operation, among other specific tasks. Similarly,client computing device(s) 102 can be selected to effectively serviceapplications 110 in order to efficiently produce and store primary data112.

Moreover, in some cases, one or more of the individual components ofinformation management system 100 can be distributed to multipleseparate computing devices. As one example, for large file systems wherethe amount of data stored in management database 146 is relativelylarge, database 146 may be migrated to or may otherwise reside on aspecialized database server (e.g., an SQL server) separate from a serverthat implements the other functions of storage manager 140. Thisdistributed configuration can provide added protection because database146 can be protected with standard database utilities (e.g., SQL logshipping or database replication) independent from other functions ofstorage manager 140. Database 146 can be efficiently replicated to aremote site for use in the event of a disaster or other data loss at theprimary site. Or database 146 can be replicated to another computingdevice within the same site, such as to a higher performance machine inthe event that a storage manager host computing device can no longerservice the needs of a growing system 100.

The distributed architecture also provides scalability and efficientcomponent utilization. FIG. 1D shows an embodiment of informationmanagement system 100 including a plurality of client computing devices102 and associated data agents 142 as well as a plurality of secondarystorage computing devices 106 and associated media agents 144.Additional components can be added or subtracted based on the evolvingneeds of system 100. For instance, depending on where bottlenecks areidentified, administrators can add additional client computing devices102, secondary storage computing devices 106, and/or secondary storagedevices 108. Moreover, where multiple fungible components are available,load balancing can be implemented to dynamically address identifiedbottlenecks. As an example, storage manager 140 may dynamically selectwhich media agents 144 and/or secondary storage devices 108 to use forstorage operations based on a processing load analysis of media agents144 and/or secondary storage devices 108, respectively.

Where system 100 includes multiple media agents 144 (see, e.g., FIG.1D), a first media agent 144 may provide failover functionality for asecond failed media agent 144. In addition, media agents 144 can bedynamically selected to provide load balancing. Each client computingdevice 102 can communicate with, among other components, any of themedia agents 144, e.g., as directed by storage manager 140. And eachmedia agent 144 may communicate with, among other components, any ofsecondary storage devices 108, e.g., as directed by storage manager 140.Thus, operations can be routed to secondary storage devices 108 in adynamic and highly flexible manner, to provide load balancing, failover,etc. Further examples of scalable systems capable of dynamic storageoperations, load balancing, and failover are provided in U.S. Pat. No.7,246,207.

While distributing functionality amongst multiple computing devices canhave certain advantages, in other contexts it can be beneficial toconsolidate functionality on the same computing device. In alternativeconfigurations, certain components may reside and execute on the samecomputing device. As such, in other embodiments, one or more of thecomponents shown in FIG. 1C may be implemented on the same computingdevice. In one configuration, a storage manager 140, one or more dataagents 142, and/or one or more media agents 144 are all implemented onthe same computing device. In other embodiments, one or more data agents142 and one or more media agents 144 are implemented on the samecomputing device, while storage manager 140 is implemented on a separatecomputing device, etc. without limitation.

Exemplary Types of Information Management Operations, Including StorageOperations

In order to protect and leverage stored data, system 100 can beconfigured to perform a variety of information management operations,which may also be referred to in some cases as storage managementoperations or storage operations. These operations can generally include(i) data movement operations, (ii) processing and data manipulationoperations, and (iii) analysis, reporting, and management operations.

Data Movement Operations, Including Secondary Copy Operations

Data movement operations are generally storage operations that involvethe copying or migration of data between different locations in system100. For example, data movement operations can include operations inwhich stored data is copied, migrated, or otherwise transferred from oneor more first storage devices to one or more second storage devices,such as from primary storage device(s) 104 to secondary storagedevice(s) 108, from secondary storage device(s) 108 to differentsecondary storage device(s) 108, from secondary storage devices 108 toprimary storage devices 104, or from primary storage device(s) 104 todifferent primary storage device(s) 104, or in some cases within thesame primary storage device 104 such as within a storage array.

Data movement operations can include by way of example, backupoperations, archive operations, information lifecycle managementoperations such as hierarchical storage management operations,replication operations (e.g., continuous data replication), snapshotoperations, deduplication or single-instancing operations, auxiliarycopy operations, disaster-recovery copy operations, and the like. Aswill be discussed, some of these operations do not necessarily createdistinct copies. Nonetheless, some or all of these operations aregenerally referred to as “secondary copy operations” for simplicity,because they involve secondary copies. Data movement also comprisesrestoring secondary copies.

Backup Operations

A backup operation creates a copy of a version of primary data 112 at aparticular point in time (e.g., one or more files or other data units).Each subsequent backup copy 116 (which is a form of secondary copy 116)may be maintained independently of the first. A backup generallyinvolves maintaining a version of the copied primary data 112 as well asbackup copies 116. Further, a backup copy in some embodiments isgenerally stored in a form that is different from the native format,e.g., a backup format. This contrasts to the version in primary data 112which may instead be stored in a format native to the sourceapplication(s) 110. In various cases, backup copies can be stored in aformat in which the data is compressed, encrypted, deduplicated, and/orotherwise modified from the original native application format. Forexample, a backup copy may be stored in a compressed backup format thatfacilitates efficient long-term storage. Backup copies 116 can haverelatively long retention periods as compared to primary data 112, whichis generally highly changeable. Backup copies 116 may be stored on mediawith slower retrieval times than primary storage device 104. Some backupcopies may have shorter retention periods than some other types ofsecondary copies 116, such as archive copies (described below). Backupsmay be stored at an offsite location.

Backup operations can include full backups, differential backups,incremental backups, “synthetic full” backups, and/or creating a“reference copy.” A full backup (or “standard full backup”) in someembodiments is generally a complete image of the data to be protected.However, because full backup copies can consume a relatively largeamount of storage, it can be useful to use a full backup copy as abaseline and only store changes relative to the full backup copyafterwards.

A differential backup operation (or cumulative incremental backupoperation) tracks and stores changes that occurred since the last fullbackup. Differential backups can grow quickly in size, but can restorerelatively efficiently because a restore can be completed in some casesusing only the full backup copy and the latest differential copy.

An incremental backup operation generally tracks and stores changessince the most recent backup copy of any type, which can greatly reducestorage utilization. In some cases, however, restoring can be lengthycompared to full or differential backups because completing a restoreoperation may involve accessing a full backup in addition to multipleincremental backups.

Synthetic full backups generally consolidate data without directlybacking up data from the client computing device. A synthetic fullbackup is created from the most recent full backup (i.e., standard orsynthetic) and subsequent incremental and/or differential backups. Theresulting synthetic full backup is identical to what would have beencreated had the last backup for the subclient been a standard fullbackup. Unlike standard full, incremental, and differential backups,however, a synthetic full backup does not actually transfer data fromprimary storage to the backup media, because it operates as a backupconsolidator. A synthetic full backup extracts the index data of eachparticipating subclient. Using this index data and the previously backedup user data images, it builds new full backup images (e.g., bitmaps),one for each subclient. The new backup images consolidate the index anduser data stored in the related incremental, differential, and previousfull backups into a synthetic backup file that fully represents thesubclient (e.g., via pointers) but does not comprise all its constituentdata.

Any of the above types of backup operations can be at the volume level,file level, or block level. Volume level backup operations generallyinvolve copying of a data volume (e.g., a logical disk or partition) asa whole. In a file-level backup, information management system 100generally tracks changes to individual files and includes copies offiles in the backup copy. For block-level backups, files are broken intoconstituent blocks, and changes are tracked at the block level. Uponrestore, system 100 reassembles the blocks into files in a transparentfashion. Far less data may actually be transferred and copied tosecondary storage devices 108 during a file-level copy than avolume-level copy. Likewise, a block-level copy may transfer less datathan a file-level copy, resulting in faster execution. However,restoring a relatively higher-granularity copy can result in longerrestore times. For instance, when restoring a block-level copy, theprocess of locating and retrieving constituent blocks can sometimes takelonger than restoring file-level backups.

A reference copy may comprise copy(ies) of selected objects from backedup data, typically to help organize data by keeping contextualinformation from multiple sources together, and/or help retain specificdata for a longer period of time, such as for legal hold needs. Areference copy generally maintains data integrity, and when the data isrestored, it may be viewed in the same format as the source data. Insome embodiments, a reference copy is based on a specialized client,individual subclient and associated information management policies(e.g., storage policy, retention policy, etc.) that are administeredwithin system 100.

Archive Operations

Because backup operations generally involve maintaining a version of thecopied primary data 112 and also maintaining backup copies in secondarystorage device(s) 108, they can consume significant storage capacity. Toreduce storage consumption, an archive operation according to certainembodiments creates an archive copy 116 by both copying and removingsource data. Or, seen another way, archive operations can involve movingsome or all of the source data to the archive destination. Thus, datasatisfying criteria for removal (e.g., data of a threshold age or size)may be removed from source storage. The source data may be primary data112 or a secondary copy 116, depending on the situation. As with backupcopies, archive copies can be stored in a format in which the data iscompressed, encrypted, deduplicated, and/or otherwise modified from theformat of the original application or source copy. In addition, archivecopies may be retained for relatively long periods of time (e.g., years)and, in some cases are never deleted. In certain embodiments, archivecopies may be made and kept for extended periods in order to meetcompliance regulations.

Archiving can also serve the purpose of freeing up space in primarystorage device(s) 104 and easing the demand on computational resourceson client computing device 102. Similarly, when a secondary copy 116 isarchived, the archive copy can therefore serve the purpose of freeing upspace in the source secondary storage device(s) 108. Examples of dataarchiving operations are provided in U.S. Pat. No. 7,107,298.

Snapshot Operations

Snapshot operations can provide a relatively lightweight, efficientmechanism for protecting data. From an end-user viewpoint, a snapshotmay be thought of as an “instant” image of primary data 112 at a givenpoint in time, and may include state and/or status information relativeto an application 110 that creates/manages primary data 112. In oneembodiment, a snapshot may generally capture the directory structure ofan object in primary data 112 such as a file or volume or other data setat a particular moment in time and may also preserve file attributes andcontents. A snapshot in some cases is created relatively quickly, e.g.,substantially instantly, using a minimum amount of file space, but maystill function as a conventional file system backup.

A “hardware snapshot” (or “hardware-based snapshot”) operation occurswhere a target storage device (e.g., a primary storage device 104 or asecondary storage device 108) performs the snapshot operation in aself-contained fashion, substantially independently, using hardware,firmware and/or software operating on the storage device itself. Forinstance, the storage device may perform snapshot operations generallywithout intervention or oversight from any of the other components ofthe system 100, e.g., a storage array may generate an “array-created”hardware snapshot and may also manage its storage, integrity,versioning, etc. In this manner, hardware snapshots can off-load othercomponents of system 100 from snapshot processing. An array may receivea request from another component to take a snapshot and then proceed toexecute the “hardware snapshot” operations autonomously, preferablyreporting success to the requesting component.

A “software snapshot” (or “software-based snapshot”) operation, on theother hand, occurs where a component in system 100 (e.g., clientcomputing device 102, etc.) implements a software layer that manages thesnapshot operation via interaction with the target storage device. Forinstance, the component executing the snapshot management software layermay derive a set of pointers and/or data that represents the snapshot.The snapshot management software layer may then transmit the same to thetarget storage device, along with appropriate instructions for writingthe snapshot. One example of a software snapshot product is MicrosoftVolume Snapshot Service (VSS), which is part of the Microsoft Windowsoperating system.

Some types of snapshots do not actually create another physical copy ofall the data as it existed at the particular point in time, but maysimply create pointers that map files and directories to specific memorylocations (e.g., to specific disk blocks) where the data resides as itexisted at the particular point in time. For example, a snapshot copymay include a set of pointers derived from the file system or from anapplication. In some other cases, the snapshot may be created at theblock-level, such that creation of the snapshot occurs without awarenessof the file system. Each pointer points to a respective stored datablock, so that collectively, the set of pointers reflect the storagelocation and state of the data object (e.g., file(s) or volume(s) ordata set(s)) at the point in time when the snapshot copy was created.

An initial snapshot may use only a small amount of disk space needed torecord a mapping or other data structure representing or otherwisetracking the blocks that correspond to the current state of the filesystem. Additional disk space is usually required only when files anddirectories change later on. Furthermore, when files change, typicallyonly the pointers which map to blocks are copied, not the blocksthemselves. For example for “copy-on-write” snapshots, when a blockchanges in primary storage, the block is copied to secondary storage orcached in primary storage before the block is overwritten in primarystorage, and the pointer to that block is changed to reflect the newlocation of that block. The snapshot mapping of file system data mayalso be updated to reflect the changed block(s) at that particular pointin time. In some other cases, a snapshot includes a full physical copyof all or substantially all of the data represented by the snapshot.Further examples of snapshot operations are provided in U.S. Pat. No.7,529,782. A snapshot copy in many cases can be made quickly and withoutsignificantly impacting primary computing resources because largeamounts of data need not be copied or moved. In some embodiments, asnapshot may exist as a virtual file system, parallel to the actual filesystem. Users in some cases gain read-only access to the record of filesand directories of the snapshot. By electing to restore primary data 112from a snapshot taken at a given point in time, users may also returnthe current file system to the state of the file system that existedwhen the snapshot was taken.

Replication Operations

Replication is another type of secondary copy operation. Some types ofsecondary copies 116 periodically capture images of primary data 112 atparticular points in time (e.g., backups, archives, and snapshots).However, it can also be useful for recovery purposes to protect primarydata 112 in a more continuous fashion, by replicating primary data 112substantially as changes occur. In some cases a replication copy can bea mirror copy, for instance, where changes made to primary data 112 aremirrored or substantially immediately copied to another location (e.g.,to secondary storage device(s) 108). By copying each write operation tothe replication copy, two storage systems are kept synchronized orsubstantially synchronized so that they are virtually identical atapproximately the same time. Where entire disk volumes are mirrored,however, mirroring can require significant amount of storage space andutilizes a large amount of processing resources.

According to some embodiments, secondary copy operations are performedon replicated data that represents a recoverable state, or “known goodstate” of a particular application running on the source system. Forinstance, in certain embodiments, known good replication copies may beviewed as copies of primary data 112. This feature allows the system todirectly access, copy, restore, back up, or otherwise manipulate thereplication copies as if they were the “live” primary data 112. This canreduce access time, storage utilization, and impact on sourceapplications 110, among other benefits. Based on known good stateinformation, system 100 can replicate sections of application data thatrepresent a recoverable state rather than rote copying of blocks ofdata. Examples of replication operations (e.g., continuous datareplication) are provided in U.S. Pat. No. 7,617,262.

Deduplication/Single-Instancing Operations

Deduplication or single-instance storage is useful to reduce the amountof non-primary data. For instance, some or all of the above-describedsecondary copy operations can involve deduplication in some fashion. Newdata is read, broken down into data portions of a selected granularity(e.g., sub-file level blocks, files, etc.), compared with correspondingportions that are already in secondary storage, and only new/changedportions are stored. Portions that already exist are represented aspointers to the already-stored data. Thus, a deduplicated secondary copy116 may comprise actual data portions copied from primary data 112 andmay further comprise pointers to already-stored data, which is generallymore storage-efficient than a full copy.

In order to streamline the comparison process, system 100 may calculateand/or store signatures (e.g., hashes or cryptographically unique IDs)corresponding to the individual source data portions and compare thesignatures to already-stored data signatures, instead of comparingentire data portions. In some cases, only a single instance of each dataportion is stored, and deduplication operations may therefore bereferred to interchangeably as “single-instancing” operations. Dependingon the implementation, however, deduplication operations can store morethan one instance of certain data portions, yet still significantlyreduce stored-data redundancy. Depending on the embodiment,deduplication portions such as data blocks can be of fixed or variablelength. Using variable length blocks can enhance deduplication byresponding to changes in the data stream, but can involve more complexprocessing. In some cases, system 100 utilizes a technique fordynamically aligning deduplication blocks based on changing content inthe data stream, as described in U.S. Pat. No. 8,364,652.

System 100 can deduplicate in a variety of manners at a variety oflocations. For instance, in some embodiments, system 100 implements“target-side” deduplication by deduplicating data at the media agent 144after being received from data agent 142. In some such cases, mediaagents 144 are generally configured to manage the deduplication process.For instance, one or more of the media agents 144 maintain acorresponding deduplication database that stores deduplicationinformation (e.g., datablock signatures). Examples of such aconfiguration are provided in U.S. Pat. No. 9,020,900. Instead of or incombination with “target-side” deduplication, “source-side” (or“client-side”) deduplication can also be performed, e.g., to reduce theamount of data to be transmitted by data agent 142 to media agent 144.Storage manager 140 may communicate with other components within system100 via network protocols and cloud service provider APIs to facilitatecloud-based deduplication/single instancing, as exemplified in U.S. Pat.No. 8,954,446. Some other deduplication/single instancing techniques aredescribed in U.S. Pat. Pub. No. 2006/0224846 and in U.S. Pat. No.9,098,495.

Information Lifecycle Management and Hierarchical Storage Management

In some embodiments, files and other data over their lifetime move frommore expensive quick-access storage to less expensive slower-accessstorage. Operations associated with moving data through various tiers ofstorage are sometimes referred to as information lifecycle management(ILM) operations.

One type of ILM operation is a hierarchical storage management (HSM)operation, which generally automatically moves data between classes ofstorage devices, such as from high-cost to low-cost storage devices. Forinstance, an HSM operation may involve movement of data from primarystorage devices 104 to secondary storage devices 108, or between tiersof secondary storage devices 108. With each tier, the storage devicesmay be progressively cheaper, have relatively slower access/restoretimes, etc. For example, movement of data between tiers may occur asdata becomes less important over time. In some embodiments, an HSMoperation is similar to archiving in that creating an HSM copy may(though not always) involve deleting some of the source data, e.g.,according to one or more criteria related to the source data. Forexample, an HSM copy may include primary data 112 or a secondary copy116 that exceeds a given size threshold or a given age threshold. Often,and unlike some types of archive copies, HSM data that is removed oraged from the source is replaced by a logical reference pointer or stub.The reference pointer or stub can be stored in the primary storagedevice 104 or other source storage device, such as a secondary storagedevice 108 to replace the deleted source data and to point to orotherwise indicate the new location in (another) secondary storagedevice 108.

For example, files are generally moved between higher and lower coststorage depending on how often the files are accessed. When a userrequests access to HSM data that has been removed or migrated, system100 uses the stub to locate the data and may make recovery of the dataappear transparent, even though the HSM data may be stored at a locationdifferent from other source data. In this manner, the data appears tothe user (e.g., in file system browsing windows and the like) as if itstill resides in the source location (e.g., in a primary storage device104). The stub may include metadata associated with the correspondingdata, so that a file system and/or application can provide someinformation about the data object and/or a limited-functionality version(e.g., a preview) of the data object.

An HSM copy may be stored in a format other than the native applicationformat (e.g., compressed, encrypted, deduplicated, and/or otherwisemodified). In some cases, copies which involve the removal of data fromsource storage and the maintenance of stub or other logical referenceinformation on source storage may be referred to generally as “on-linearchive copies.” On the other hand, copies which involve the removal ofdata from source storage without the maintenance of stub or otherlogical reference information on source storage may be referred to as“off-line archive copies.” Examples of HSM and ILM techniques areprovided in U.S. Pat. No. 7,343,453.

Auxiliary Copy Operations

An auxiliary copy is generally a copy of an existing secondary copy 116.For instance, an initial secondary copy 116 may be derived from primarydata 112 or from data residing in secondary storage subsystem 118,whereas an auxiliary copy is generated from the initial secondary copy116. Auxiliary copies provide additional standby copies of data and mayreside on different secondary storage devices 108 than the initialsecondary copies 116. Thus, auxiliary copies can be used for recoverypurposes if initial secondary copies 116 become unavailable. Exemplaryauxiliary copy techniques are described in further detail in U.S. Pat.No. 8,230,195.

Disaster-Recovery Copy Operations

System 100 may also make and retain disaster recovery copies, often assecondary, high-availability disk copies. System 100 may createsecondary copies and store them at disaster recovery locations usingauxiliary copy or replication operations, such as continuous datareplication technologies. Depending on the particular data protectiongoals, disaster recovery locations can be remote from the clientcomputing devices 102 and primary storage devices 104, remote from someor all of the secondary storage devices 108, or both.

Data Manipulation, Including Encryption and Compression

Data manipulation and processing may include encryption and compressionas well as integrity marking and checking, formatting for transmission,formatting for storage, etc. Data may be manipulated “client-side” bydata agent 142 as well as “target-side” by media agent 144 in the courseof creating secondary copy 116, or conversely in the course of restoringdata from secondary to primary.

Encryption Operations

System 100 in some cases is configured to process data (e.g., files orother data objects, primary data 112, secondary copies 116, etc.),according to an appropriate encryption algorithm (e.g., Blowfish,Advanced Encryption Standard (AES), Triple Data Encryption Standard(3-DES), etc.) to limit access and provide data security. System 100 insome cases encrypts the data at the client level, such that clientcomputing devices 102 (e.g., data agents 142) encrypt the data prior totransferring it to other components, e.g., before sending the data tomedia agents 144 during a secondary copy operation. In such cases,client computing device 102 may maintain or have access to an encryptionkey or passphrase for decrypting the data upon restore. Encryption canalso occur when media agent 144 creates auxiliary copies or archivecopies. Encryption may be applied in creating a secondary copy 116 of apreviously unencrypted secondary copy 116, without limitation. Infurther embodiments, secondary storage devices 108 can implementbuilt-in, high performance hardware-based encryption.

Compression Operations

Similar to encryption, system 100 may also or alternatively compressdata in the course of generating a secondary copy 116. Compressionencodes information such that fewer bits are needed to represent theinformation as compared to the original representation. Compressiontechniques are well known in the art. Compression operations may applyone or more data compression algorithms. Compression may be applied increating a secondary copy 116 of a previously uncompressed secondarycopy, e.g., when making archive copies or disaster recovery copies. Theuse of compression may result in metadata that specifies the nature ofthe compression, so that data may be uncompressed on restore ifappropriate.

Data Analysis, Reporting, and Management Operations

Data analysis, reporting, and management operations can differ from datamovement operations in that they do not necessarily involve copying,migration or other transfer of data between different locations in thesystem. For instance, data analysis operations may involve processing(e.g., offline processing) or modification of already stored primarydata 112 and/or secondary copies 116. However, in some embodiments dataanalysis operations are performed in conjunction with data movementoperations. Some data analysis operations include content indexingoperations and classification operations which can be useful inleveraging data under management to enhance search and other features.

Classification Operations/Content Indexing

In some embodiments, information management system 100 analyzes andindexes characteristics, content, and metadata associated with primarydata 112 (“online content indexing”) and/or secondary copies 116(“off-line content indexing”). Content indexing can identify files orother data objects based on content (e.g., user-defined keywords orphrases, other keywords/phrases that are not defined by a user, etc.),and/or metadata (e.g., email metadata such as “to,” “from,” “cc,” “bcc,”attachment name, received time, etc.). Content indexes may be searchedand search results may be restored.

System 100 generally organizes and catalogues the results into a contentindex, which may be stored within media agent database 152, for example.The content index can also include the storage locations of or pointerreferences to indexed data in primary data 112 and/or secondary copies116. Results may also be stored elsewhere in system 100 (e.g., inprimary storage device 104 or in secondary storage device 108). Suchcontent index data provides storage manager 140 or other components withan efficient mechanism for locating primary data 112 and/or secondarycopies 116 of data objects that match particular criteria, thus greatlyincreasing the search speed capability of system 100. For instance,search criteria can be specified by a user through user interface 158 ofstorage manager 140. Moreover, when system 100 analyzes data and/ormetadata in secondary copies 116 to create an “off-line content index,”this operation has no significant impact on the performance of clientcomputing devices 102 and thus does not take a toll on the productionenvironment. Examples of content indexing techniques are provided inU.S. Pat. No. 8,170,995.

One or more components, such as a content index engine, can beconfigured to scan data and/or associated metadata for classificationpurposes to populate a database (or other data structure) ofinformation, which can be referred to as a “data classificationdatabase” or a “metabase.” Depending on the embodiment, the dataclassification database(s) can be organized in a variety of differentways, including centralization, logical sub-divisions, and/or physicalsub-divisions. For instance, one or more data classification databasesmay be associated with different subsystems or tiers within system 100.As an example, there may be a first metabase associated with primarystorage subsystem 117 and a second metabase associated with secondarystorage subsystem 118. In other cases, metabase(s) may be associatedwith individual components, e.g., client computing devices 102 and/ormedia agents 144. In some embodiments, a data classification databasemay reside as one or more data structures within management database146, may be otherwise associated with storage manager 140, and/or mayreside as a separate component. In some cases, metabase(s) may beincluded in separate database(s) and/or on separate storage device(s)from primary data 112 and/or secondary copies 116, such that operationsrelated to the metabase(s) do not significantly impact performance onother components of system 100. In other cases, metabase(s) may bestored along with primary data 112 and/or secondary copies 116. Files orother data objects can be associated with identifiers (e.g., tagentries, etc.) to facilitate searches of stored data objects. Among anumber of other benefits, the metabase can also allow efficient,automatic identification of files or other data objects to associatewith secondary copy or other information management operations. Forinstance, a metabase can dramatically improve the speed with whichsystem 100 can search through and identify data as compared to otherapproaches that involve scanning an entire file system. Examples ofmetabases and data classification operations are provided in U.S. Pat.Nos. 7,734,669 and 7,747,579.

Management and Reporting Operations

Certain embodiments leverage the integrated ubiquitous nature of system100 to provide useful system-wide management and reporting. Operationsmanagement can generally include monitoring and managing the health andperformance of system 100 by, without limitation, performing errortracking, generating granular storage/performance metrics (e.g., jobsuccess/failure information, deduplication efficiency, etc.), generatingstorage modeling and costing information, and the like. As an example,storage manager 140 or another component in system 100 may analyzetraffic patterns and suggest and/or automatically route data to minimizecongestion. In some embodiments, the system can generate predictionsrelating to storage operations or storage operation information. Suchpredictions, which may be based on a trending analysis, may predictvarious network operations or resource usage, such as network trafficlevels, storage media use, use of bandwidth of communication links, useof media agent components, etc. Further examples of traffic analysis,trend analysis, prediction generation, and the like are described inU.S. Pat. No. 7,343,453.

In some configurations having a hierarchy of storage operation cells, amaster storage manager 140 may track the status of subordinate cells,such as the status of jobs, system components, system resources, andother items, by communicating with storage managers 140 (or othercomponents) in the respective storage operation cells. Moreover, themaster storage manager 140 may also track status by receiving periodicstatus updates from the storage managers 140 (or other components) inthe respective cells regarding jobs, system components, systemresources, and other items. In some embodiments, a master storagemanager 140 may store status information and other information regardingits associated storage operation cells and other system information inits management database 146 and/or index 150 (or in another location).The master storage manager 140 or other component may also determinewhether certain storage-related or other criteria are satisfied, and mayperform an action or trigger event (e.g., data migration) in response tothe criteria being satisfied, such as where a storage threshold is metfor a particular volume, or where inadequate protection exists forcertain data. For instance, data from one or more storage operationcells is used to dynamically and automatically mitigate recognizedrisks, and/or to advise users of risks or suggest actions to mitigatethese risks. For example, an information management policy may specifycertain requirements (e.g., that a storage device should maintain acertain amount of free space, that secondary copies should occur at aparticular interval, that data should be aged and migrated to otherstorage after a particular period, that data on a secondary volumeshould always have a certain level of availability and be restorablewithin a given time period, that data on a secondary volume may bemirrored or otherwise migrated to a specified number of other volumes,etc.). If a risk condition or other criterion is triggered, the systemmay notify the user of these conditions and may suggest (orautomatically implement) a mitigation action to address the risk. Forexample, the system may indicate that data from a primary copy 112should be migrated to a secondary storage device 108 to free up space onprimary storage device 104. Examples of the use of risk factors andother triggering criteria are described in U.S. Pat. No. 7,343,453.

In some embodiments, system 100 may also determine whether a metric orother indication satisfies particular storage criteria sufficient toperform an action. For example, a storage policy or other definitionmight indicate that a storage manager 140 should initiate a particularaction if a storage metric or other indication drops below or otherwisefails to satisfy specified criteria such as a threshold of dataprotection. In some embodiments, risk factors may be quantified intocertain measurable service or risk levels. For example, certainapplications and associated data may be considered to be more importantrelative to other data and services. Financial compliance data, forexample, may be of greater importance than marketing materials, etc.Network administrators may assign priority values or “weights” tocertain data and/or applications corresponding to the relativeimportance. The level of compliance of secondary copy operationsspecified for these applications may also be assigned a certain value.Thus, the health, impact, and overall importance of a service may bedetermined, such as by measuring the compliance value and calculatingthe product of the priority value and the compliance value to determinethe “service level” and comparing it to certain operational thresholdsto determine whether it is acceptable. Further examples of the servicelevel determination are provided in U.S. Pat. No. 7,343,453.

System 100 may additionally calculate data costing and data availabilityassociated with information management operation cells. For instance,data received from a cell may be used in conjunction withhardware-related information and other information about system elementsto determine the cost of storage and/or the availability of particulardata. Exemplary information generated could include how fast aparticular department is using up available storage space, how long datawould take to recover over a particular pathway from a particularsecondary storage device, costs over time, etc. Moreover, in someembodiments, such information may be used to determine or predict theoverall cost associated with the storage of certain information. Thecost associated with hosting a certain application may be based, atleast in part, on the type of media on which the data resides, forexample. Storage devices may be assigned to a particular costcategories, for example. Further examples of costing techniques aredescribed in U.S. Pat. No. 7,343,453.

Any of the above types of information (e.g., information related totrending, predictions, job, cell or component status, risk, servicelevel, costing, etc.) can generally be provided to users via userinterface 158 in a single integrated view or console (not shown). Reporttypes may include: scheduling, event management, media management anddata aging. Available reports may also include backup history, dataaging history, auxiliary copy history, job history, library and drive,media in library, restore history, and storage policy, etc., withoutlimitation. Such reports may be specified and created at a certain pointin time as a system analysis, forecasting, or provisioning tool.Integrated reports may also be generated that illustrate storage andperformance metrics, risks and storage costing information. Moreover,users may create their own reports based on specific needs. Userinterface 158 can include an option to graphically depict the variouscomponents in the system using appropriate icons. As one example, userinterface 158 may provide a graphical depiction of primary storagedevices 104, secondary storage devices 108, data agents 142 and/or mediaagents 144, and their relationship to one another in system 100.

In general, the operations management functionality of system 100 canfacilitate planning and decision-making. For example, in someembodiments, a user may view the status of some or all jobs as well asthe status of each component of information management system 100. Usersmay then plan and make decisions based on this data. For instance, auser may view high-level information regarding secondary copy operationsfor system 100, such as job status, component status, resource status(e.g., communication pathways, etc.), and other information. The usermay also drill down or use other means to obtain more detailedinformation regarding a particular component, job, or the like. Furtherexamples are provided in U.S. Pat. No. 7,343,453.

System 100 can also be configured to perform system-wide e-discoveryoperations in some embodiments. In general, e-discovery operationsprovide a unified collection and search capability for data in thesystem, such as data stored in secondary storage devices 108 (e.g.,backups, archives, or other secondary copies 116). For example, system100 may construct and maintain a virtual repository for data stored insystem 100 that is integrated across source applications 110, differentstorage device types, etc. According to some embodiments, e-discoveryutilizes other techniques described herein, such as data classificationand/or content indexing.

Information Management Policies

An information management policy 148 can include a data structure orother information source that specifies a set of parameters (e.g.,criteria and rules) associated with secondary copy and/or otherinformation management operations.

One type of information management policy 148 is a “storage policy.”According to certain embodiments, a storage policy generally comprises adata structure or other information source that defines (or includesinformation sufficient to determine) a set of preferences or othercriteria for performing information management operations. Storagepolicies can include one or more of the following: (1) what data will beassociated with the storage policy, e.g., subclient; (2) a destinationto which the data will be stored; (3) datapath information specifyinghow the data will be communicated to the destination; (4) the type ofsecondary copy operation to be performed; and (5) retention informationspecifying how long the data will be retained at the destination (see,e.g., FIG. 1E). Data associated with a storage policy can be logicallyorganized into subclients, which may represent primary data 112 and/orsecondary copies 116. A subclient may represent static or dynamicassociations of portions of a data volume. Subclients may representmutually exclusive portions. Thus, in certain embodiments, a portion ofdata may be given a label and the association is stored as a staticentity in an index, database or other storage location. Subclients mayalso be used as an effective administrative scheme of organizing dataaccording to data type, department within the enterprise, storagepreferences, or the like. Depending on the configuration, subclients cancorrespond to files, folders, virtual machines, databases, etc. In oneexemplary scenario, an administrator may find it preferable to separatee-mail data from financial data using two different subclients.

A storage policy can define where data is stored by specifying a targetor destination storage device (or group of storage devices). Forinstance, where the secondary storage device 108 includes a group ofdisk libraries, the storage policy may specify a particular disk libraryfor storing the subclients associated with the policy. As anotherexample, where the secondary storage devices 108 include one or moretape libraries, the storage policy may specify a particular tape libraryfor storing the subclients associated with the storage policy, and mayalso specify a drive pool and a tape pool defining a group of tapedrives and a group of tapes, respectively, for use in storing thesubclient data. While information in the storage policy can bestatically assigned in some cases, some or all of the information in thestorage policy can also be dynamically determined based on criteria setforth in the storage policy. For instance, based on such criteria, aparticular destination storage device(s) or other parameter of thestorage policy may be determined based on characteristics associatedwith the data involved in a particular secondary copy operation, deviceavailability (e.g., availability of a secondary storage device 108 or amedia agent 144), network status and conditions (e.g., identifiedbottlenecks), user credentials, and the like.

Datapath information can also be included in the storage policy. Forinstance, the storage policy may specify network pathways and componentsto utilize when moving the data to the destination storage device(s). Insome embodiments, the storage policy specifies one or more media agents144 for conveying data associated with the storage policy between thesource and destination. A storage policy can also specify the type(s) ofassociated operations, such as backup, archive, snapshot, auxiliarycopy, or the like. Furthermore, retention parameters can specify howlong the resulting secondary copies 116 will be kept (e.g., a number ofdays, months, years, etc.), perhaps depending on organizational needsand/or compliance criteria.

When adding a new client computing device 102, administrators canmanually configure information management policies 148 and/or othersettings, e.g., via user interface 158. However, this can be an involvedprocess resulting in delays, and it may be desirable to begin dataprotection operations quickly, without awaiting human intervention.Thus, in some embodiments, system 100 automatically applies a defaultconfiguration to client computing device 102. As one example, when oneor more data agent(s) 142 are installed on a client computing device102, the installation script may register the client computing device102 with storage manager 140, which in turn applies the defaultconfiguration to the new client computing device 102. In this manner,data protection operations can begin substantially immediately. Thedefault configuration can include a default storage policy, for example,and can specify any appropriate information sufficient to begin dataprotection operations. This can include a type of data protectionoperation, scheduling information, a target secondary storage device108, data path information (e.g., a particular media agent 144), and thelike.

Another type of information management policy 148 is a “schedulingpolicy,” which specifies when and how often to perform operations.Scheduling parameters may specify with what frequency (e.g., hourly,weekly, daily, event-based, etc.) or under what triggering conditionssecondary copy or other information management operations are to takeplace. Scheduling policies in some cases are associated with particularcomponents, such as a subclient, client computing device 102, and thelike.

Another type of information management policy 148 is an “audit policy”(or “security policy”), which comprises preferences, rules and/orcriteria that protect sensitive data in system 100. For example, anaudit policy may define “sensitive objects” which are files or dataobjects that contain particular keywords (e.g., “confidential,” or“privileged”) and/or are associated with particular keywords (e.g., inmetadata) or particular flags (e.g., in metadata identifying a documentor email as personal, confidential, etc.). An audit policy may furtherspecify rules for handling sensitive objects. As an example, an auditpolicy may require that a reviewer approve the transfer of any sensitiveobjects to a cloud storage site, and that if approval is denied for aparticular sensitive object, the sensitive object should be transferredto a local primary storage device 104 instead. To facilitate thisapproval, the audit policy may further specify how a secondary storagecomputing device 106 or other system component should notify a reviewerthat a sensitive object is slated for transfer.

Another type of information management policy 148 is a “provisioningpolicy,” which can include preferences, priorities, rules, and/orcriteria that specify how client computing devices 102 (or groupsthereof) may utilize system resources, such as available storage oncloud storage and/or network bandwidth. A provisioning policy specifies,for example, data quotas for particular client computing devices 102(e.g., a number of gigabytes that can be stored monthly, quarterly orannually). Storage manager 140 or other components may enforce theprovisioning policy. For instance, media agents 144 may enforce thepolicy when transferring data to secondary storage devices 108. If aclient computing device 102 exceeds a quota, a budget for the clientcomputing device 102 (or associated department) may be adjustedaccordingly or an alert may trigger.

While the above types of information management policies 148 aredescribed as separate policies, one or more of these can be generallycombined into a single information management policy 148. For instance,a storage policy may also include or otherwise be associated with one ormore scheduling, audit, or provisioning policies or operationalparameters thereof. Moreover, while storage policies are typicallyassociated with moving and storing data, other policies may beassociated with other types of information management operations. Thefollowing is a non-exhaustive list of items that information managementpolicies 148 may specify:

-   -   schedules or other timing information, e.g., specifying when        and/or how often to perform information management operations;    -   the type of secondary copy 116 and/or copy format (e.g.,        snapshot, backup, archive, HSM, etc.);    -   a location or a class or quality of storage for storing        secondary copies 116 (e.g., one or more particular secondary        storage devices 108);    -   preferences regarding whether and how to encrypt, compress,        deduplicate, or otherwise modify or transform secondary copies        116;    -   which system components and/or network pathways (e.g., preferred        media agents 144) should be used to perform secondary storage        operations;    -   resource allocation among different computing devices or other        system components used in performing information management        operations (e.g., bandwidth allocation, available storage        capacity, etc.);    -   whether and how to synchronize or otherwise distribute files or        other data objects across multiple computing devices or hosted        services; and    -   retention information specifying the length of time primary data        112 and/or secondary copies 116 should be retained, e.g., in a        particular class or tier of storage devices, or within the        system 100.

Information management policies 148 can additionally specify or dependon historical or current criteria that may be used to determine whichrules to apply to a particular data object, system component, orinformation management operation, such as:

-   -   frequency with which primary data 112 or a secondary copy 116 of        a data object or metadata has been or is predicted to be used,        accessed, or modified;    -   time-related factors (e.g., aging information such as time since        the creation or modification of a data object);    -   deduplication information (e.g., hashes, data blocks,        deduplication block size, deduplication efficiency or other        metrics);    -   an estimated or historic usage or cost associated with different        components (e.g., with secondary storage devices 108);    -   the identity of users, applications 110, client computing        devices 102 and/or other computing devices that created,        accessed, modified, or otherwise utilized primary data 112 or        secondary copies 116;    -   a relative sensitivity (e.g., confidentiality, importance) of a        data object, e.g., as determined by its content and/or metadata;    -   the current or historical storage capacity of various storage        devices;    -   the current or historical network capacity of network pathways        connecting various components within the storage operation cell;    -   access control lists or other security information; and    -   the content of a particular data object (e.g., its textual        content) or of metadata associated with the data object.

Exemplary Storage Policy and Secondary Copy Operations

FIG. 1E includes a data flow diagram depicting performance of secondarycopy operations by an embodiment of information management system 100,according to an exemplary storage policy 148A. System 100 includes astorage manager 140, a client computing device 102 having a file systemdata agent 142A and an email data agent 142B operating thereon, aprimary storage device 104, two media agents 144A, 144B, and twosecondary storage devices 108: a disk library 108A and a tape library108B. As shown, primary storage device 104 includes primary data 112A,which is associated with a logical grouping of data associated with afile system (“file system subclient”), and primary data 112B, which is alogical grouping of data associated with email (“email subclient”). Thetechniques described with respect to FIG. 1E can be utilized inconjunction with data that is otherwise organized as well.

As indicated by the dashed box, the second media agent 144B and tapelibrary 108B are “off-site,” and may be remotely located from the othercomponents in system 100 (e.g., in a different city, office building,etc.). Indeed, “off-site” may refer to a magnetic tape located in remotestorage, which must be manually retrieved and loaded into a tape driveto be read. In this manner, information stored on the tape library 108Bmay provide protection in the event of a disaster or other failure atthe main site(s) where data is stored.

The file system subclient 112A in certain embodiments generallycomprises information generated by the file system and/or operatingsystem of client computing device 102, and can include, for example,file system data (e.g., regular files, file tables, mount points, etc.),operating system data (e.g., registries, event logs, etc.), and thelike. The e-mail subclient 112B can include data generated by an e-mailapplication operating on client computing device 102, e.g., mailboxinformation, folder information, emails, attachments, associateddatabase information, and the like. As described above, the subclientscan be logical containers, and the data included in the correspondingprimary data 112A and 112B may or may not be stored contiguously.

The exemplary storage policy 148A includes backup copy preferences orrule set 160, disaster recovery copy preferences or rule set 162, andcompliance copy preferences or rule set 164. Backup copy rule set 160specifies that it is associated with file system subclient 166 and emailsubclient 168. Each of subclients 166 and 168 are associated with theparticular client computing device 102. Backup copy rule set 160 furtherspecifies that the backup operation will be written to disk library 108Aand designates a particular media agent 144A to convey the data to disklibrary 108A. Finally, backup copy rule set 160 specifies that backupcopies created according to rule set 160 are scheduled to be generatedhourly and are to be retained for 30 days. In some other embodiments,scheduling information is not included in storage policy 148A and isinstead specified by a separate scheduling policy.

Disaster recovery copy rule set 162 is associated with the same twosubclients 166 and 168. However, disaster recovery copy rule set 162 isassociated with tape library 108B, unlike backup copy rule set 160.Moreover, disaster recovery copy rule set 162 specifies that a differentmedia agent, namely 144B, will convey data to tape library 108B.Disaster recovery copies created according to rule set 162 will beretained for 60 days and will be generated daily. Disaster recoverycopies generated according to disaster recovery copy rule set 162 canprovide protection in the event of a disaster or other catastrophic dataloss that would affect the backup copy 116A maintained on disk library108A.

Compliance copy rule set 164 is only associated with the email subclient168, and not the file system subclient 166. Compliance copies generatedaccording to compliance copy rule set 164 will therefore not includeprimary data 112A from the file system subclient 166. For instance, theorganization may be under an obligation to store and maintain copies ofemail data for a particular period of time (e.g., 10 years) to complywith state or federal regulations, while similar regulations do notapply to file system data. Compliance copy rule set 164 is associatedwith the same tape library 108B and media agent 144B as disasterrecovery copy rule set 162, although a different storage device or mediaagent could be used in other embodiments. Finally, compliance copy ruleset 164 specifies that the copies it governs will be generated quarterlyand retained for 10 years.

Secondary Copy Jobs

A logical grouping of secondary copy operations governed by a rule setand being initiated at a point in time may be referred to as a“secondary copy job” (and sometimes may be called a “backup job,” eventhough it is not necessarily limited to creating only backup copies).Secondary copy jobs may be initiated on demand as well. Steps 1-9 belowillustrate three secondary copy jobs based on storage policy 148A.

Referring to FIG. 1E, at step 1, storage manager 140 initiates a backupjob according to the backup copy rule set 160, which logically comprisesall the secondary copy operations necessary to effectuate rules 160 instorage policy 148A every hour, including steps 1-4 occurring hourly.For instance, a scheduling service running on storage manager 140accesses backup copy rule set 160 or a separate scheduling policyassociated with client computing device 102 and initiates a backup jobon an hourly basis. Thus, at the scheduled time, storage manager 140sends instructions to client computing device 102 (i.e., to both dataagent 142A and data agent 142B) to begin the backup job.

At step 2, file system data agent 142A and email data agent 142B onclient computing device 102 respond to instructions from storage manager140 by accessing and processing the respective subclient primary data112A and 112B involved in the backup copy operation, which can be foundin primary storage device 104. Because the secondary copy operation is abackup copy operation, the data agent(s) 142A, 142B may format the datainto a backup format or otherwise process the data suitable for a backupcopy.

At step 3, client computing device 102 communicates the processed filesystem data (e.g., using file system data agent 142A) and the processedemail data (e.g., using email data agent 142B) to the first media agent144A according to backup copy rule set 160, as directed by storagemanager 140. Storage manager 140 may further keep a record in managementdatabase 146 of the association between media agent 144A and one or moreof: client computing device 102, file system subclient 112A, file systemdata agent 142A, email subclient 112B, email data agent 142B, and/orbackup copy 116A.

The target media agent 144A receives the data-agent-processed data fromclient computing device 102, and at step 4 generates and conveys backupcopy 116A to disk library 108A to be stored as backup copy 116A, againat the direction of storage manager 140 and according to backup copyrule set 160. Media agent 144A can also update its index 153 to includedata and/or metadata related to backup copy 116A, such as informationindicating where the backup copy 116A resides on disk library 108A,where the email copy resides, where the file system copy resides, dataand metadata for cache retrieval, etc. Storage manager 140 may similarlyupdate its index 150 to include information relating to the secondarycopy operation, such as information relating to the type of operation, aphysical location associated with one or more copies created by theoperation, the time the operation was performed, status informationrelating to the operation, the components involved in the operation, andthe like. In some cases, storage manager 140 may update its index 150 toinclude some or all of the information stored in index 153 of mediaagent 144A. At this point, the backup job may be considered complete.After the 30-day retention period expires, storage manager 140 instructsmedia agent 144A to delete backup copy 116A from disk library 108A andindexes 150 and/or 153 are updated accordingly.

At step 5, storage manager 140 initiates another backup job for adisaster recovery copy according to the disaster recovery rule set 162.Illustratively this includes steps 5-7 occurring daily for creatingdisaster recovery copy 1168. Illustratively, and by way of illustratingthe scalable aspects and off-loading principles embedded in system 100,disaster recovery copy 1168 is based on backup copy 116A and not onprimary data 112A and 112B.

At step 6, illustratively based on instructions received from storagemanager 140 at step 5, the specified media agent 144B retrieves the mostrecent backup copy 116A from disk library 108A.

At step 7, again at the direction of storage manager 140 and asspecified in disaster recovery copy rule set 162, media agent 144B usesthe retrieved data to create a disaster recovery copy 1168 and store itto tape library 108B. In some cases, disaster recovery copy 1168 is adirect, mirror copy of backup copy 116A, and remains in the backupformat. In other embodiments, disaster recovery copy 1168 may be furthercompressed or encrypted, or may be generated in some other manner, suchas by using primary data 112A and 112B from primary storage device 104as sources. The disaster recovery copy operation is initiated once a dayand disaster recovery copies 1168 are deleted after 60 days; indexes 153and/or 150 are updated accordingly when/after each informationmanagement operation is executed and/or completed. The present backupjob may be considered completed.

At step 8, storage manager 140 initiates another backup job according tocompliance rule set 164, which performs steps 8-9 quarterly to createcompliance copy 116C. For instance, storage manager 140 instructs mediaagent 144B to create compliance copy 116C on tape library 108B, asspecified in the compliance copy rule set 164.

At step 9 in the example, compliance copy 116C is generated usingdisaster recovery copy 1168 as the source. This is efficient, becausedisaster recovery copy resides on the same secondary storage device andthus no network resources are required to move the data. In otherembodiments, compliance copy 116C is instead generated using primarydata 1128 corresponding to the email subclient or using backup copy 116Afrom disk library 108A as source data. As specified in the illustratedexample, compliance copies 116C are created quarterly, and are deletedafter ten years, and indexes 153 and/or 150 are kept up-to-dateaccordingly.

Exemplary Applications of Storage Policies—Information GovernancePolicies and Classification

Again referring to FIG. 1E, storage manager 140 may permit a user tospecify aspects of storage policy 148A. For example, the storage policycan be modified to include information governance policies to define howdata should be managed in order to comply with a certain regulation orbusiness objective. The various policies may be stored, for example, inmanagement database 146. An information governance policy may align withone or more compliance tasks that are imposed by regulations or businessrequirements. Examples of information governance policies might includea Sarbanes-Oxley policy, a HIPAA policy, an electronic discovery(e-discovery) policy, and so on.

Information governance policies allow administrators to obtain differentperspectives on an organization's online and offline data, without theneed for a dedicated data silo created solely for each differentviewpoint. As described previously, the data storage systems hereinbuild an index that reflects the contents of a distributed data set thatspans numerous clients and storage devices, including both primary dataand secondary copies, and online and offline copies. An organization mayapply multiple information governance policies in a top-down manner overthat unified data set and indexing schema in order to view andmanipulate the data set through different lenses, each of which isadapted to a particular compliance or business goal. Thus, for example,by applying an e-discovery policy and a Sarbanes-Oxley policy, twodifferent groups of users in an organization can conduct two verydifferent analyses of the same underlying physical set of data/copies,which may be distributed throughout the information management system.

An information governance policy may comprise a classification policy,which defines a taxonomy of classification terms or tags relevant to acompliance task and/or business objective. A classification policy mayalso associate a defined tag with a classification rule. Aclassification rule defines a particular combination of criteria, suchas users who have created, accessed or modified a document or dataobject; file or application types; content or metadata keywords; clientsor storage locations; dates of data creation and/or access; reviewstatus or other status within a workflow (e.g., reviewed orun-reviewed); modification times or types of modifications; and/or anyother data attributes in any combination, without limitation. Aclassification rule may also be defined using other classification tagsin the taxonomy. The various criteria used to define a classificationrule may be combined in any suitable fashion, for example, via Booleanoperators, to define a complex classification rule. As an example, ane-discovery classification policy might define a classification tag“privileged” that is associated with documents or data objects that (1)were created or modified by legal department staff, or (2) were sent toor received from outside counsel via email, or (3) contain one of thefollowing keywords: “privileged” or “attorney” or “counsel,” or otherlike terms. Accordingly, all these documents or data objects will beclassified as “privileged.”

One specific type of classification tag, which may be added to an indexat the time of indexing, is an “entity tag.” An entity tag may be, forexample, any content that matches a defined data mask format. Examplesof entity tags might include, e.g., social security numbers (e.g., anynumerical content matching the formatting mask XXX-XX-XXXX), credit cardnumbers (e.g., content having a 13-16 digit string of numbers), SKUnumbers, product numbers, etc. A user may define a classification policyby indicating criteria, parameters or descriptors of the policy via agraphical user interface, such as a form or page with fields to befilled in, pull-down menus or entries allowing one or more of severaloptions to be selected, buttons, sliders, hypertext links or other knownuser interface tools for receiving user input, etc. For example, a usermay define certain entity tags, such as a particular product number orproject ID. In some implementations, the classification policy can beimplemented using cloud-based techniques. For example, the storagedevices may be cloud storage devices, and the storage manager 140 mayexecute cloud service provider API over a network to classify datastored on cloud storage devices.

Restore Operations from Secondary Copies

While not shown in FIG. 1E, at some later point in time, a restoreoperation can be initiated involving one or more of secondary copies116A, 116B, and 116C. A restore operation logically takes a selectedsecondary copy 116, reverses the effects of the secondary copy operationthat created it, and stores the restored data to primary storage where aclient computing device 102 may properly access it as primary data. Amedia agent 144 and an appropriate data agent 142 (e.g., executing onthe client computing device 102) perform the tasks needed to complete arestore operation. For example, data that was encrypted, compressed,and/or deduplicated in the creation of secondary copy 116 will becorrespondingly rehydrated (reversing deduplication), uncompressed, andunencrypted into a format appropriate to primary data. Metadata storedwithin or associated with the secondary copy 116 may be used during therestore operation. In general, restored data should be indistinguishablefrom other primary data 112. Preferably, the restored data has fullyregained the native format that may make it immediately usable byapplication 110.

As one example, a user may manually initiate a restore of backup copy116A, e.g., by interacting with user interface 158 of storage manager140 or with a web-based console with access to system 100. Storagemanager 140 may accesses data in its index 150 and/or managementdatabase 146 (and/or the respective storage policy 148A) associated withthe selected backup copy 116A to identify the appropriate media agent144A and/or secondary storage device 108A where the secondary copyresides. The user may be presented with a representation (e.g., stub,thumbnail, listing, etc.) and metadata about the selected secondarycopy, in order to determine whether this is the appropriate copy to berestored, e.g., date that the original primary data was created. Storagemanager 140 will then instruct media agent 144A and an appropriate dataagent 142 on the target client computing device 102 to restore secondarycopy 116A to primary storage device 104. A media agent may be selectedfor use in the restore operation based on a load balancing algorithm, anavailability based algorithm, or other criteria. The selected mediaagent, e.g., 144A, retrieves secondary copy 116A from disk library 108A.For instance, media agent 144A may access its index 153 to identify alocation of backup copy 116A on disk library 108A, or may accesslocation information residing on disk library 108A itself.

In some cases a backup copy 116A that was recently created or accessed,may be cached to speed up the restore operation. In such a case, mediaagent 144A accesses a cached version of backup copy 116A residing inindex 153, without having to access disk library 108A for some or all ofthe data. Once it has retrieved backup copy 116A, the media agent 144Acommunicates the data to the requesting client computing device 102.Upon receipt, file system data agent 142A and email data agent 142B mayunpack (e.g., restore from a backup format to the native applicationformat) the data in backup copy 116A and restore the unpackaged data toprimary storage device 104. In general, secondary copies 116 may berestored to the same volume or folder in primary storage device 104 fromwhich the secondary copy was derived; to another storage location orclient computing device 102; to shared storage, etc. In some cases, thedata may be restored so that it may be used by an application 110 of adifferent version/vintage from the application that created the originalprimary data 112.

Exemplary Secondary Copy Formatting

The formatting and structure of secondary copies 116 can vary dependingon the embodiment. In some cases, secondary copies 116 are formatted asa series of logical data units or “chunks” (e.g., 512 MB, 1 GB, 2 GB, 4GB, or 8 GB chunks). This can facilitate efficient communication andwriting to secondary storage devices 108, e.g., according to resourceavailability. For example, a single secondary copy 116 may be written ona chunk-by-chunk basis to one or more secondary storage devices 108. Insome cases, users can select different chunk sizes, e.g., to improvethroughput to tape storage devices. Generally, each chunk can include aheader and a payload. The payload can include files (or other dataunits) or subsets thereof included in the chunk, whereas the chunkheader generally includes metadata relating to the chunk, some or all ofwhich may be derived from the payload. For example, during a secondarycopy operation, media agent 144, storage manager 140, or other componentmay divide files into chunks and generate headers for each chunk byprocessing the files. Headers can include a variety of information suchas file and/or volume identifier(s), offset(s), and/or other informationassociated with the payload data items, a chunk sequence number, etc.Importantly, in addition to being stored with secondary copy 116 onsecondary storage device 108, chunk headers can also be stored to index153 of the associated media agent(s) 144 and/or to index 150 associatedwith storage manager 140. This can be useful for providing fasterprocessing of secondary copies 116 during browsing, restores, or otheroperations. In some cases, once a chunk is successfully transferred to asecondary storage device 108, the secondary storage device 108 returnsan indication of receipt, e.g., to media agent 144 and/or storagemanager 140, which may update their respective indexes 153, 150accordingly. During restore, chunks may be processed (e.g., by mediaagent 144) according to the information in the chunk header toreassemble the files.

Data can also be communicated within system 100 in data channels thatconnect client computing devices 102 to secondary storage devices 108.These data channels can be referred to as “data streams,” and multipledata streams can be employed to parallelize an information managementoperation, improving data transfer rate, among other advantages. Exampledata formatting techniques including techniques involving datastreaming, chunking, and the use of other data structures in creatingsecondary copies are described in U.S. Pat. Nos. 7,315,923, 8,156,086,and 8,578,120.

FIGS. 1F and 1G are diagrams of example data streams 170 and 171,respectively, which may be employed for performing informationmanagement operations. Referring to FIG. 1F, data agent 142 forms datastream 170 from source data associated with a client computing device102 (e.g., primary data 112). Data stream 170 is composed of multiplepairs of stream header 172 and stream data (or stream payload) 174. Datastreams 170 and 171 shown in the illustrated example are for asingle-instanced storage operation, and a stream payload 174 thereforemay include both single-instance (SI) data and/or non-SI data. A streamheader 172 includes metadata about the stream payload 174. This metadatamay include, for example, a length of the stream payload 174, anindication of whether the stream payload 174 is encrypted, an indicationof whether the stream payload 174 is compressed, an archive fileidentifier (ID), an indication of whether the stream payload 174 issingle instanceable, and an indication of whether the stream payload 174is a start of a block of data.

Referring to FIG. 1G, data stream 171 has the stream header 172 andstream payload 174 aligned into multiple data blocks. In this example,the data blocks are of size 64 KB. The first two stream header 172 andstream payload 174 pairs comprise a first data block of size 64 KB. Thefirst stream header 172 indicates that the length of the succeedingstream payload 174 is 63 KB and that it is the start of a data block.The next stream header 172 indicates that the succeeding stream payload174 has a length of 1 KB and that it is not the start of a new datablock. Immediately following stream payload 174 is a pair comprising anidentifier header 176 and identifier data 178. The identifier header 176includes an indication that the succeeding identifier data 178 includesthe identifier for the immediately previous data block. The identifierdata 178 includes the identifier that the data agent 142 generated forthe data block. The data stream 171 also includes other stream header172 and stream payload 174 pairs, which may be for SI data and/or non-SIdata.

FIG. 1H is a diagram illustrating data structures 180 that may be usedto store blocks of SI data and non-SI data on a storage device (e.g.,secondary storage device 108). According to certain embodiments, datastructures 180 do not form part of a native file system of the storagedevice. Data structures 180 include one or more volume folders 182, oneor more chunk folders 184/185 within the volume folder 182, and multiplefiles within chunk folder 184. Each chunk folder 184/185 includes ametadata file 186/187, a metadata index file 188/189, one or morecontainer files 190/191/193, and a container index file 192/194.Metadata file 186/187 stores non-SI data blocks as well as links to SIdata blocks stored in container files. Metadata index file 188/189stores an index to the data in the metadata file 186/187. Containerfiles 190/191/193 store SI data blocks. Container index file 192/194stores an index to container files 190/191/193. Among other things,container index file 192/194 stores an indication of whether acorresponding block in a container file 190/191/193 is referred to by alink in a metadata file 186/187. For example, data block B2 in thecontainer file 190 is referred to by a link in metadata file 187 inchunk folder 185. Accordingly, the corresponding index entry incontainer index file 192 indicates that data block B2 in container file190 is referred to. As another example, data block B1 in container file191 is referred to by a link in metadata file 187, and so thecorresponding index entry in container index file 192 indicates thatthis data block is referred to.

As an example, data structures 180 illustrated in FIG. 1H may have beencreated as a result of separate secondary copy operations involving twoclient computing devices 102. For example, a first secondary copyoperation on a first client computing device 102 could result in thecreation of the first chunk folder 184, and a second secondary copyoperation on a second client computing device 102 could result in thecreation of the second chunk folder 185. Container files 190/191 in thefirst chunk folder 184 would contain the blocks of SI data of the firstclient computing device 102. If the two client computing devices 102have substantially similar data, the second secondary copy operation onthe data of the second client computing device 102 would result in mediaagent 144 storing primarily links to the data blocks of the first clientcomputing device 102 that are already stored in the container files190/191. Accordingly, while a first secondary copy operation may resultin storing nearly all of the data subject to the operation, subsequentsecondary storage operations involving similar data may result insubstantial data storage space savings, because links to already storeddata blocks can be stored instead of additional instances of datablocks.

If the operating system of the secondary storage computing device 106 onwhich media agent 144 operates supports sparse files, then when mediaagent 144 creates container files 190/191/193, it can create them assparse files. A sparse file is a type of file that may include emptyspace (e.g., a sparse file may have real data within it, such as at thebeginning of the file and/or at the end of the file, but may also haveempty space in it that is not storing actual data, such as a contiguousrange of bytes all having a value of zero). Having container files190/191/193 be sparse files allows media agent 144 to free up space incontainer files 190/191/193 when blocks of data in container files190/191/193 no longer need to be stored on the storage devices. In someexamples, media agent 144 creates a new container file 190/191/193 whena container file 190/191/193 either includes 100 blocks of data or whenthe size of the container file 190 exceeds 50 MB. In other examples,media agent 144 creates a new container file 190/191/193 when acontainer file 190/191/193 satisfies other criteria (e.g., it containsfrom approx. 100 to approx. 1000 blocks or when its size exceedsapproximately 50 MB to 1 GB). In some cases, a file on which a secondarycopy operation is performed may comprise a large number of data blocks.For example, a 100 MB file may comprise 400 data blocks of size 256 KB.If such a file is to be stored, its data blocks may span more than onecontainer file, or even more than one chunk folder. As another example,a database file of 20 GB may comprise over 40,000 data blocks of size512 KB. If such a database file is to be stored, its data blocks willlikely span multiple container files, multiple chunk folders, andpotentially multiple volume folders. Restoring such files may requireaccessing multiple container files, chunk folders, and/or volume foldersto obtain the requisite data blocks.

Using Backup Data for Replication and Disaster Recovery (“LiveSynchronization”)

There is an increased demand to off-load resource intensive informationmanagement tasks (e.g., data replication tasks) away from productiondevices (e.g., physical or virtual client computing devices) in order tomaximize production efficiency. At the same time, enterprises expectaccess to readily-available up-to-date recovery copies in the event offailure, with little or no production downtime.

FIG. 2A illustrates a system 200 configured to address these and otherissues by using backup or other secondary copy data to synchronize asource subsystem 201 (e.g., a production site) with a destinationsubsystem 203 (e.g., a failover site). Such a technique can be referredto as “live synchronization” and/or “live synchronization replication.”In the illustrated embodiment, the source client computing devices 202 ainclude one or more virtual machines (or “VMs”) executing on one or morecorresponding VM host computers 205 a, though the source need not bevirtualized. The destination site 203 may be at a location that isremote from the production site 201, or may be located in the same datacenter, without limitation. One or more of the production site 201 anddestination site 203 may reside at data centers at known geographiclocations, or alternatively may operate “in the cloud.”

The synchronization can be achieved by generally applying an ongoingstream of incremental backups from the source subsystem 201 to thedestination subsystem 203, such as according to what can be referred toas an “incremental forever” approach. FIG. 2A illustrates an embodimentof a data flow which may be orchestrated at the direction of one or morestorage managers (not shown). At step 1, the source data agent(s) 242 aand source media agent(s) 244 a work together to write backup or othersecondary copies of the primary data generated by the source clientcomputing devices 202 a into the source secondary storage device(s) 208a. At step 2, the backup/secondary copies are retrieved by the sourcemedia agent(s) 244 a from secondary storage. At step 3, source mediaagent(s) 244 a communicate the backup/secondary copies across a networkto the destination media agent(s) 244 b in destination subsystem 203.

As shown, the data can be copied from source to destination in anincremental fashion, such that only changed blocks are transmitted, andin some cases multiple incremental backups are consolidated at thesource so that only the most current changed blocks are transmitted toand applied at the destination. An example of live synchronization ofvirtual machines using the “incremental forever” approach is found inU.S. Patent Application No. 62/265,339 entitled “Live Synchronizationand Management of Virtual Machines across Computing and VirtualizationPlatforms and Using Live Synchronization to Support Disaster Recovery.”Moreover, a deduplicated copy can be employed to further reduce networktraffic from source to destination. For instance, the system can utilizethe deduplicated copy techniques described in U.S. Pat. No. 9,239,687,entitled “Systems and Methods for Retaining and Using Data BlockSignatures in Data Protection Operations.”

At step 4, destination media agent(s) 244 b write the receivedbackup/secondary copy data to the destination secondary storagedevice(s) 208 b. At step 5, the synchronization is completed when thedestination media agent(s) and destination data agent(s) 242 b restorethe backup/secondary copy data to the destination client computingdevice(s) 202 b. The destination client computing device(s) 202 b may bekept “warm” awaiting activation in case failure is detected at thesource. This synchronization/replication process can incorporate thetechniques described in U.S. patent application Ser. No. 14/721,971,entitled “Replication Using Deduplicated Secondary Copy Data.”

Where the incremental backups are applied on a frequent, on-going basis,the synchronized copies can be viewed as mirror or replication copies.Moreover, by applying the incremental backups to the destination site203 using backup or other secondary copy data, the production site 201is not burdened with the synchronization operations. Because thedestination site 203 can be maintained in a synchronized “warm” state,the downtime for switching over from the production site 201 to thedestination site 203 is substantially less than with a typical restorefrom secondary storage. Thus, the production site 201 may flexibly andefficiently fail over, with minimal downtime and with relativelyup-to-date data, to a destination site 203, such as a cloud-basedfailover site. The destination site 203 can later be reversesynchronized back to the production site 201, such as after repairs havebeen implemented or after the failure has passed.

Integrating With the Cloud Using File System Protocols

Given the ubiquity of cloud computing, it can be increasingly useful toprovide data protection and other information management services in ascalable, transparent, and highly plug-able fashion. FIG. 2B illustratesan information management system 200 having an architecture thatprovides such advantages, and incorporates use of a standard file systemprotocol between primary and secondary storage subsystems 217, 218. Asshown, the use of the network file system (NFS) protocol (or any anotherappropriate file system protocol such as that of the Common InternetFile System (CIFS)) allows data agent 242 to be moved from the primarystorage subsystem 217 to the secondary storage subsystem 218. Forinstance, as indicated by the dashed box 206 around data agent 242 andmedia agent 244, data agent 242 can co-reside with media agent 244 onthe same server (e.g., a secondary storage computing device such ascomponent 106), or in some other location in secondary storage subsystem218.

Where NFS is used, for example, secondary storage subsystem 218allocates an NFS network path to the client computing device 202 or toone or more target applications 210 running on client computing device202. During a backup or other secondary copy operation, the clientcomputing device 202 mounts the designated NFS path and writes data tothat NFS path. The NFS path may be obtained from NFS path data 215stored locally at the client computing device 202, and which may be acopy of or otherwise derived from NFS path data 219 stored in thesecondary storage subsystem 218.

Write requests issued by client computing device(s) 202 are received bydata agent 242 in secondary storage subsystem 218, which translates therequests and works in conjunction with media agent 244 to process andwrite data to a secondary storage device(s) 208, thereby creating abackup or other secondary copy. Storage manager 240 can include apseudo-client manager 217, which coordinates the process by, among otherthings, communicating information relating to client computing device202 and application 210 (e.g., application type, client computing deviceidentifier, etc.) to data agent 242, obtaining appropriate NFS path datafrom the data agent 242 (e.g., NFS path information), and deliveringsuch data to client computing device 202.

Conversely, during a restore or recovery operation client computingdevice 202 reads from the designated NFS network path, and the readrequest is translated by data agent 242. The data agent 242 then workswith media agent 244 to retrieve, re-process (e.g., re-hydrate,decompress, decrypt), and forward the requested data to client computingdevice 202 using NFS.

By moving specialized software associated with system 200 such as dataagent 242 off the client computing devices 202, the illustrativearchitecture effectively decouples the client computing devices 202 fromthe installed components of system 200, improving both scalability andplug-ability of system 200. Indeed, the secondary storage subsystem 218in such environments can be treated simply as a read/write NFS targetfor primary storage subsystem 217, without the need for informationmanagement software to be installed on client computing devices 202. Asone example, an enterprise implementing a cloud production computingenvironment can add VM client computing devices 202 without installingand configuring specialized information management software on theseVMs. Rather, backups and restores are achieved transparently, where thenew VMs simply write to and read from the designated NFS path. Anexample of integrating with the cloud using file system protocols orso-called “infinite backup” using NFS share is found in U.S. PatentApplication No. 62/294,920, entitled “Data Protection Operations Basedon Network Path Information.” Examples of improved data restorationscenarios based on network-path information, including using storedbackups effectively as primary data sources, may be found in U.S. PatentApplication No. 62/297,057, entitled “Data Restoration Operations Basedon Network Path Information.”

Highly Scalable Managed Data Pool Architecture

Enterprises are seeing explosive data growth in recent years, often fromvarious applications running in geographically distributed locations.FIG. 2C shows a block diagram of an example of a highly scalable,managed data pool architecture useful in accommodating such data growth.The illustrated system 200, which may be referred to as a “web-scale”architecture according to certain embodiments, can be readilyincorporated into both open compute/storage and common-cloudarchitectures.

The illustrated system 200 includes a grid 245 of media agents 244logically organized into a control tier 231 and a secondary or storagetier 233. Media agents assigned to the storage tier 233 can beconfigured to manage a secondary storage pool 208 as a deduplicationstore, and be configured to receive client write and read requests fromthe primary storage subsystem 217, and direct those requests to thesecondary tier 233 for servicing. For instance, media agents CMA1-CMA3in the control tier 231 maintain and consult one or more deduplicationdatabases 247, which can include deduplication information (e.g., datablock hashes, data block links, file containers for deduplicated files,etc.) sufficient to read deduplicated files from secondary storage pool208 and write deduplicated files to secondary storage pool 208. Forinstance, system 200 can incorporate any of the deduplication systemsand methods shown and described in U.S. Pat. No. 9,020,900, entitled“Distributed Deduplicated Storage System,” and U.S. Pat. Pub. No.2014/0201170, entitled “High Availability Distributed DeduplicatedStorage System.”

Media agents SMA1-SMA6 assigned to the secondary tier 233 receive writeand read requests from media agents CMA1-CMA3 in control tier 231, andaccess secondary storage pool 208 to service those requests. Mediaagents CMA1-CMA3 in control tier 231 can also communicate with secondarystorage pool 208, and may execute read and write requests themselves(e.g., in response to requests from other control media agentsCMA1-CMA3) in addition to issuing requests to media agents in secondarytier 233. Moreover, while shown as separate from the secondary storagepool 208, deduplication database(s) 247 can in some cases reside instorage devices in secondary storage pool 208.

As shown, each of the media agents 244 (e.g., CMA1-CMA3, SMA1-SMA6,etc.) in grid 245 can be allocated a corresponding dedicated partition251A-251I, respectively, in secondary storage pool 208. Each partition251 can include a first portion 253 containing data associated with(e.g., stored by) media agent 244 corresponding to the respectivepartition 251. System 200 can also implement a desired level ofreplication, thereby providing redundancy in the event of a failure of amedia agent 244 in grid 245. Along these lines, each partition 251 canfurther include a second portion 255 storing one or more replicationcopies of the data associated with one or more other media agents 244 inthe grid.

System 200 can also be configured to allow for seamless addition ofmedia agents 244 to grid 245 via automatic configuration. As oneillustrative example, a storage manager (not shown) or other appropriatecomponent may determine that it is appropriate to add an additional nodeto control tier 231, and perform some or all of the following: (i)assess the capabilities of a newly added or otherwise availablecomputing device as satisfying a minimum criteria to be configured as orhosting a media agent in control tier 231; (ii) confirm that asufficient amount of the appropriate type of storage exists to supportan additional node in control tier 231 (e.g., enough disk drive capacityexists in storage pool 208 to support an additional deduplicationdatabase 247); (iii) install appropriate media agent software on thecomputing device and configure the computing device according to apre-determined template; (iv) establish a partition 251 in the storagepool 208 dedicated to the newly established media agent 244; and (v)build any appropriate data structures (e.g., an instance ofdeduplication database 247). An example of highly scalable managed datapool architecture or so-called web-scale architecture for storage anddata management is found in U.S. Patent Application No. 62/273,286entitled “Redundant and Robust Distributed Deduplication Data StorageSystem.”

The embodiments and components thereof disclosed in FIGS. 2A, 2B, and2C, as well as those in FIGS. 1A-1H, may be implemented in anycombination and permutation to satisfy data storage management andinformation management needs at one or more locations and/or datacenters.

Summarization of Email on a Client Computing Device Based on ContentContribution to an Email Thread Using Classification and Word FrequencyConsiderations

FIG. 3A is a block diagram illustrating some salient portions of astorage management system 300 for summarization and processing of emailon a client computing device, according to an illustrative embodiment ofthe present invention. Data storage management system 300 (“system 300”)is an embodiment of an information management system that is enhancedfor summarization and processing of email at a client computing devicebased on relative content contributions made to an email thread byindividual emails in the thread. System 300 illustratively comprises:primary storage subsystem 117 comprising any number of fixed and/ormobile client computing devices 302; secondary storage subsystem 118;and storage manager 140.

Client computing device 302 is any kind of fixed or mobile computingdevice analogous to client computing device 102, and accordinglyexecutes one or more data agents 142 (not shown here); and also executesa client email application and additional functionality associated withit for operating in system 300, as shown in FIG. 3B. Client computingdevice 302 comprises functionality for processing emails and summarizingemail threads based on content contributions made by individual emailsin each thread. The email-thread summaries is illustratively presentedto users in a special user interface that comprises additionalfunctionality based on content gleaned from emails in the thread, e.g.,upcoming deadlines, customer information, etc.

Moreover, the email processing disclosed herein comprises a utility forautomatically storing email attachments to a so-called “edge drive” 380on (or associated with) the client computing device, wherein thecontents of the edge drive are automatically backed up by system 300.For sensitive data that may be included in such attachments, this kindof operation provides an important additional level of data protection,apart from the email system that handles the emails, thus bringing theattachments within the ambit of the data storage management system andits superior data protection features.

FIG. 3B is a block diagram depicting some salient details of a clientcomputing device 302, which is a component of system 300. Clientcomputing device 302 comprises: email client application 310 comprisingcontent summarizer 352 and user interface 354; email application filefolder 312 comprising summarizer parameters 362, “important”word-frequency table 364-IM, “regular” word-frequency table 356-R,collected contacts 366, and collected customer account and systeminformation 368; and edge drive 380. Console 390 is also depicted incommunication with client computing device 302.

Email client application 310 is a computer program installed andexecuting on client computing device 302, and is implemented asexecutable software and/or firmware. Examples of email clientapplications include Microsoft Outlook brand, Mozilla Thunderbird brand,etc. The email client application is illustratively coupled to andretrieves emails from an email server application, such as MicrosoftExchange brand (not shown here). Unlike email client applications thatare well known in the art, email client application 310 according to theillustrative embodiment further comprises additional functionality,including content summarizing capability (e.g., content summarizer 362)and new user interface features (e.g., user interface 354), as describedin more detail below.

Email application file folder 312 is a component of client computingdevice 302 and is associated with email client application 310. Filefolder 312 illustratively comprises data that is (in whole or in part)used by, generated by, collected by, and stored by email clientapplication 310 to file folder 312. The data in file folder 312 isembodied as a number of distinct data structures, e.g., 362, 364, 366,368, etc. In some alternative embodiments, file folder 312 may beembodied as a unified data structure, such as a table or database,without limitation. In some embodiments, file folder 312 may furthercomprise email-application-related data structures that are well knownin the art and which are not connected with the present invention. Insome alternative illustrative embodiments, file folder 312 is separateand distinct from application-related files and file folders in theprior art. Email application file folder 312 is accessible to the userof client computing device 302 as part of a surrounding file system (notshown), such as Microsoft Windows Explorer brand.

Content summarizer 352 is a functional component of email clientapplication 310. Content summarizer 352 is embodied as a plug-inenhancement to an existing client email application, such as MicrosoftOutlook. In some alternative embodiments it is a linked library coupledto the email client application. When it executes according to theillustrative embodiment, content summarizer 352 is largely responsiblefor: analyzing emails, based on certain input summarizer parameters(e.g., 362); classifying emails by importance; generating word-frequencytables (e.g., 364-IM and 364-R) from the analyzed emails; collectingcontent from the analyzed emails (e.g., contacts 366 and customeraccount and system information 368); analyzing content and generatingemail-thread summaries; presenting email-thread summaries to users(e.g., via user interface 354); and taking responsive actions based onuser inputs (e.g., date-time selection, contact selection, etc.), etc.,without limitation and in any combination. Content summarizer 354 alsostores email attachments to edge drive 380, which falls under the ambitof data storage policies that govern how the data on the edge drive isprotected apart from how the emails are treated in application 310.

User interface 354 is a functional component of email client application310. User interface 354 is embodied as a plug-in enhancement to anexisting client email application, such as Microsoft Outlook. In somealternative embodiments it is a linked library coupled to the emailclient application. When it executes according to the illustrativeembodiment, user interface 354 is largely responsible for presentingemail-thread summaries to users, receiving user input such as aselection of a date-time from a menu or a selection of a user who ispart of a thread summary, presenting a link or stub of an emailattachment that has been stored to edge drive 380, etc. withoutlimitation and win any combination. User interface 354 appears as a newand distinct “Summarizer” pane, enhancing the native user interface ofemail client application 310. The illustrative Summarizer pane includes:an email-thread content summary for a given email thread; a sub-panecomprising date-time choices gleaned by content summarizer 352 from theemails in the thread, which allow the user to select a date-time, whichthen causes an appropriate calendar entry to be created in the user'scalendar; one or more hyperlinks to other relevant information gleanedfrom the emails in the thread, such as contact information for peoplewhose content appears in the thread summary and/or customer systemand/or account information that may be referenced in the thread summary(e.g., the storage cell ID for the system being discussed in the emailthread); a sentiment indicator for the content in the email thread(e.g., an angry emoji, a happy emoji, etc.); and any combination thereofwithout limitation.

Content summarizer 352 and user interface 354 are shown herein asdistinct components to ease understanding of the present disclosure,however, alternative embodiments are also possible within the scope ofthe present invention. For example, these components may be embodied asa unified module, may be further subdivided, may be layered on existingemail client application code, may be implemented as a linked library,or may be a logical construct whose functionality is distributed throughone or more other functional modules of the email client, such as a userinterface module, and in any combination thereof.

Summarizer parameters 362 is a data structure comprising any number ofparameters needed for purposes of classification, analysis, andsummarization of emails according to the illustrative embodiment.Example summarizer parameters include: a sliding window of time (e.g.,30 days, 90 days, etc.) that forms the basis for determining wordfrequency in a baseline set of user emails; whether word frequencyshould be classified as “important” versus “regular” or should becalculated collectively; how many sentences should be used in anemail-thread summary; how weights should be assigned to emails in athread; whether sentiment indicators should be computed and presented inthread summaries; a list of “stop words”; whether email attachmentsshould be stored to edge drive 380, and if so, whether they should bereplaced with stubs and/or pointers; etc. Other summarizer parameters362 are described in more detail elsewhere herein.

“Stop words” generally include common words that are to be left out orfiltered out before analyzing email content, such as “a” “the” “is” “at”“which” “ten” “thus” etc. The concept of stop words is well known in theart, especially in regard to natural language processing. However, thelist of stop words may vary from application to application, dependingon what kind of content is being analyzed and why. Therefore, forpurposes of the illustrative embodiment, a list of stop words will beincluded in summarization parameters 362, and the list willillustratively be used in email classification and generatingword-frequency tables as well as in analyzing emails to generateemail-thread summaries. Any list of stop words available in the art maybe used here.

Word-frequency table 364-IM is a data structure that comprises a set ofwords, other than stop words, that content summarizer 352 determines tobe “important” according to the illustrative embodiment, and whosefrequency is calculated from a baseline set of the emails during a givensliding window of time, e.g., the previous calendar month.Illustratively, words found in emails classified as important will beclassified as important words. The presence of a word in the importantword-frequency table 364-IM may affect a weighting assigned to the wordin the course of generating an email-thread summary (e.g., importantwords may weigh more than regular words). See, e.g., equation 2C herein.Word-frequency table 364-IM is illustratively organized as a table, butmay take any suitable form, whether alone or in combination withword-frequency table 364-R.

Word-frequency table 356-R is a data structure that comprises a set ofwords, other than stop words, that content summarizer 352 determines tobe “regular” or “not-important” according to the illustrativeembodiment, and whose frequency is calculated from a baseline set of theemails during a given sliding window of time, e.g., the previouscalendar month. Illustratively, words found in emails classified asregular or not-important will be classified as regular words, unlesspre-empted. The presence of a word in the important word-frequency table364-IM causes the same word to be excluded from regular word-frequencytable 356-R. The presence of a word in the regular word-frequency table364-R may affect a weighting assigned to the word in the course ofgenerating an email-thread summary (e.g., regular words may weigh lessthan important words). See, e.g., equation 2C herein. Word-frequencytable 364-R is illustratively organized as a table, but may take anysuitable form, whether alone or in combination with word-frequency table364-IM.

Collected contacts 366 is a data structure comprising user contactinformation collected from or in conjunction with emails in a givenemail thread. For example, in the course of analyzing the email thread,content summarizer 352 may collect senders' respective email addressesand signature blocks, which are stored to contacts 366. When a threadsummary is presented which contains sentences gleaned from the sourceemails, each sentence may be accompanied by a hyperlink to the sender'scontact information in contacts 366 data structure. Collected contacts366 may take any suitable form. Additional contact information may beextracted from other sources (not shown) such as a customer database, acorporate directory, etc.

Collected customer account and system information 368 is a datastructure comprising customer-related information collected from emailsin a given email thread. For example, in the course of analyzing theemail thread, content summarizer 352 may collect information aboutcustomer systems or accounts that are referenced in the emails, whichare stored to contacts 366. In some cases, the information gleaned fromthe email may be used to extract further details from a customerdatabase (not shown), which may be stored to data structure 368 forready access in preparing thread summaries. When a thread summary ispresented which contains sentences gleaned from the source emails, eachsentence may be accompanied by a hyperlink to the detailed customerinformation referenced in the sentence, e.g., a storage cell ID withphysical address plus contact name and number; an email address; an IPaddress for a storage manager; a geographic location of a system orcomponent; etc., without limitation. Collected customer account andsystem information 368 may take any suitable format.

Edge drive 380 is a storage device that is logically part of clientcomputing device 302, e.g., a local disk or a partition of a local disk.In some alternative embodiments, edge drive 380 is physically on anothercomputing device, but is logically configured on client computing device302 so that it may act as a data repository. Edge drive 380 maylogically comprise a plurality of storage devices without limitation.Edge drive 380 is a logical component of data storage management system300 and is therefore governed by information management policies, suchas storage policies, that control when and how data stored to edge drive380 is backed up and whereto. For example, data on edge drive 380 may bebacked up every 12 hours to a secondary storage device in secondarystorage subsystem 118 according to an exemplary storage policy 148.Thus, email attachments stored to edge drive 380 by email clientapplication 310 (e.g., using content summarizer 352) would be backed upevery 12 hours according to the governing storage policy 148. Any numberand type of storage policies may govern the contents of edge drive 380,e.g., hourly backups for documents and daily backups for media files,etc.

Edge drive 380 can be used as a repository of data, allowing data copiedto edge drive 380 to be available to the user on that client computingdevice 302 or other client computers. For example, users can configureedge drive 380 on a desktop computer, copy files to edge drive 380, andthose files are then accessible from a laptop, and/or through a webinterface or web console. When files in edge drive 380 are edited, thechanges appear on all the user's edge drive enabled devices. Files inedge drive 380 are protected under the ambit of data storage managementsystem 300, so users can retrieve files from edge drive 380 to anotherlocation even if the original files are lost. Commvault Systems, Inc. ofTinton Falls, N.J., USA provides an example implementation of edge drive380 under the “Edge Drive” brand.

Console 390 is a component well known in the art, which, according tothe illustrative embodiment, displays to a user an interface such asuser interface 354. Console 390 may be a computing device in its ownright or may be a “dumb terminal” connected to a network or to clientcomputing device 302. Console 390 need not be part of system 300.

FIG. 4 depicts some salient operations of a method 400 according to anillustrative embodiment of the present invention. In general, method 400is executed by client computing device 302. This may occur in the courseof installing, upgrading, and/or executing email client application 310,content summarizer 352, and/or user interface 354.

At block 402, client computing device 302 receives summarizer parameters362. These parameters may be received from storage manager 140 and/ormay be part of the installation package of email client application 310and/or content summarizer 352. Some parameters may be administrable,such as the sliding window period (e.g., previous 7 days, previous 30days, the previous calendar month, etc.). Some parameters may be fixed,such as a “stop word” list. Some parameters are embodied as a variablewhose value is obtained by executing an equation, such as an emailweight or a word weight; in such a case, the equation is part ofsummarizer parameters 362, e.g., equations 1, 2A, 2B, 2C, 3A, 3B, 3B-1,4, and 5 herein.

At block 404, client computing device 302 performs training operationsusing an applicable window period as defined in the summarizerparameters 362, e.g., previous 30 days. The window period changes overtime, e.g., monthly as a new window of time takes effect. In somealternative embodiments, the window period is static such that thepresent training operations execute only when the client emailapplication 310 and/or summarizer 352 is installed or upgraded. Moredetails are given in a subsequent figure.

At block 406, client computing device 302 receives a plurality of emailmessages (e.g., overnight). The email messages received in the presentblock may be from any number of senders and may comprise any content,and furthermore may form one or more distinct email threads. An emailthread (or “thread” or “conversation” or “topic thread”) is well knownin the art and generally refers to a logical grouping of emails thatoriginated with one email and includes replies to the original andsubsequent emails. A thread may comprise emails to/from any number ofsenders and may extend over any period of time. An email thread maycomprise emails sent by the present user. Thus the user may or may notbe a participant in any given email thread.

At block 408, client computing device 302 generates and presents athread summary (based on content contributions of individual emails) ofeach email thread in the received plurality of incoming email messages.More details are given in a subsequent figure. After block 408, controlmay pass back to block 404 for a renewed training exercise, e.g., toapply a new sliding window for example when a new month begins and thesliding window is defined as the preceding calendar month. Control alsomay pass back to block 406 for receiving and processing further emails.Method 408 also may end here.

FIG. 5 depicts some salient sub-operations of block 404 in method 400.In general, block 404 is directed at client computing device 302 (e.g.,using content summarizer 352) performing training operations using anapplicable window period as defined in the summarizer parameters 362.This block executes whenever a new window period applies, e.g., when thewindow period is defined as the preceding calendar month and a newcalendar month begins; when the window period is defined as 7 days and anew calendar week begins, etc., without limitation.

At block 502, client computing device 302 identifies a proper trainingcorpus for the training operations. The training corpus comprises abaseline set of emails to be analyzed in the applicable window,including received and sent emails. For example, when the window periodis defined as the preceding calendar month and a new calendar monthbegins, all emails received and sent by the user of client computingdevice 302 during the preceding calendar month are identified as thetraining corpus.

At block 504, client computing device 302 classifies emails in thebaseline set as important versus regular (or not-important). Theclassification is based on: (a) user behavior (e.g., read/not-read;response interval/no-response; and/or follow-up flags entered forreceived emails, etc.); and/or (b) addressing (e.g., to individualrecipient vs. CC/group). According to the illustrative embodiment,certain emails are classified as important based on objectivecharacteristics of the emails, which may arise from recipient behaviorand/or sender behavior, e.g., message marked as “read” or marked forfollow-up.

For example, emails that are classified as important illustrativelyinclude: emails the user reads (marked as “read”), optionally readwithin a certain time period after receiving the email; emails with abelow-median user response interval or below some other predefinedtiming threshold, e.g., less than 1 hour, speediest 25% of responses,etc.; emails flagged by the user for follow-up or otherwise marked bythe user as interesting or important, depending on the features of theemail client application 310. Furthermore, emails that are addresseddirectly to the user rather than to a group alias also may be classifiedas important or may contribute to the likelihood they will be classifiedas important, i.e., how the email is addressed contributes to theimportant versus not-important classification.

Emails that do not meet these criteria are classified as regular ornot-important. Although classifying the baseline email set in importantversus regular categories is preferred and provides weighting factorslater on, this operation may be skipped, resulting in global wordfrequencies rather than within the important/regular classifications. Insome embodiments, the classification may be divided differently, basedon a different set of email characteristics, e.g., ignoring whether theemail is marked read or not. In some embodiments, the emails may beclassified into more than two categories, e.g., regular, important, andcritical, wherein critical emails fall below a very tight responsewindow, e.g., less than 10 minutes. As explained in blocks 506 and 508,a word frequency will be analyzed according to email classification,e.g., important word frequency and regular word frequency.

At block 506, client computing device 302 generates a word-frequencytable (e.g., 364-IM) from emails in the applicable window that areclassified as important. For example, after dropping all stop words,salutations, and signature blocks, the substantive words found in theset of emails classified as important will be placed in a word-frequencytable 364-IM. The table will associate each substantive word with itsfrequency in the set of important emails. For example, the word “patent”may have a frequency of 1:300 or 0.5% or 0.005.

At block 508, client computing device 302 generates a word-frequencytable (e.g., 364-R) from emails in the applicable window that areclassified as regular. For example, after dropping all stop words,salutations, and signature blocks, the substantive words found in theset of emails classified as regular will be placed in a word-frequencytable 364-R. The table will associate each substantive word with itsfrequency in the set of regular emails. For example, the word “contract”may have a frequency of 1:100 or 1% or 0.01. In some embodiments, thecontents of the important word-frequency table 364-IM pre-empt theregular word-frequency table 364-R such that substantive words thatappear in the important word-frequency table 364-IM are dropped in theregular-word analysis even if they appear in regular emails. In somealternative embodiments, such words are included in the regular-wordanalysis when they appear in regular emails.

At block 510, client computing device 302 stores the word-frequencytable(s) 364 for ready access during summarization of email threads.Illustratively, word-frequency table(s) 364 are stored locally, e.g., tolocal disk or in a cache of client computing device 302. As shown later,the word frequency may be used in computing certain word weights and/orintersection scores in the course of generating a thread summary. See,e.g., equations 2C and 3B-1 herein.

FIG. 6 depicts some salient sub-operations of block 408 in method 400.In general, block 408 is directed at client computing device 302generating and presenting a thread summary. According to theillustrative embodiment, the thread summary is based on relative contentcontributions of individual emails in each email thread.

At block 602, client computing device 302 groups emails into threads.For each email-thread client computing device 302 executes the remainingillustrative blocks, e.g., 604 through 614.

At block 604, client computing device 302 analyzes the relative contentcontribution of individual emails to generate a thread summary of therespective email-thread. More details are given in a subsequent figure.

At block 606, client computing device 302 collects contact informationabout email-thread participants, e.g., email senders. Thus, the name,email address, title, and other organizational information (withoutlimitation) about the sender of each email in the thread are collectedhere. Some of this information may be obtained from other sources, suchas a corporate directory (not shown), which may be accessible to clientcomputing device 302. Some of this information may be obtained byprocessing signature blocks in the emails themselves. Contactinformation 366 is stored locally (e.g., in cache) in the course ofpreparing the thread summary and may be used when presenting the threadsummary, e.g., via hyperlinks in the thread summary to allow the user todisplay the contact information on demand. In some embodiments, thepresent block executes after the thread summary is generated andcollects only the contact information needed for the sentences in thethread summary.

At block 608, client computing device 302 collects customer account andsystem information 368 (“customer information”) based on email content.Examples of customer account and system information may include datastorage cell ID, customer identifier or email address, customerlocation, customer account number(s), customer contact information,geographical location of a system and/or component, etc., withoutlimitation. For example, based on parsing certain terms in an email,e.g., a data storage cell ID or a customer identifier, client computingdevice 302 may obtain additional information from other sources, such asa customer database or a services database or a contracts database (notshown). Customer information 368 is stored locally (e.g., in cache) inthe course of preparing the thread summary and may be used whenpresenting the thread summary, e.g., via hyperlinks in the threadsummary to allow the user to display the hyperlinked information ondemand. In some embodiments, the present block executes after the threadsummary is generated and collects only the contact information neededfor the sentences in the thread summary.

At block 610, client computing device 302 displays the thread summary(e.g., via user interface 354). The thread summary illustrativelyincludes options (e.g., hyperlinks) for additionally displaying contactand customer information from data structures 366 and 368, which werecollected at blocks 606 and 608. The presentation of the thread summarymay take any form suitable to the accompanying email client application310. Illustratively, a distinct pane is created adjacent to the inboxpane, which shows thread summaries. In some embodiments, the threadsummaries may be shown within the inbox as distinct entities. A threadsummary is illustratively presented in a format similar to online chats,wherein each sentence in the summary is identified by sender. The threadsummary preferably lists the summary sentences in chronological order,whether forward or reverse chronological order (based on summarizerparameters 362). For an illustrative example of a thread contentsummary, see FIG. 8.

At block 612, client computing device 302 may optionally: (a) provideappointment (or commitment dates) suggestions based on dates it parsedfrom the body of emails in the email-thread; (b) receive the user'schoice of an appointment/commitment; and add the chosenappointment/commitment as a calendar event in the user's onlinecalendar. An illustrative example (although empty and lacking anyapplicable choices) may be seen in FIG. 8 at block 803. In order topresent the appointment/commitment choices, client computing device 302may recognize date-time terms in the body of the email in the thread andmay parse them accordingly. For example, a first email may suggest acode submit date of Oct. 1, 2015. Another email may counter-propose analternative date of Oct. 2, 2015. Another email may further suggest Oct.3, 2015. According to the illustrative embodiment, client computingdevice 302 may provide suggestions to the user by populating theillustrative “Commitment” box with the three dates, Oct. 1, Oct. 2, andOct. 3, 2015. The user may then check the desired date, e.g., October3^(rd), which in turn will cause a corresponding calendar entry to bepopulated in the user's calendar for October 3^(rd). A time of daycomponent may also be included with the dates, e.g., October 14 at 9:00am, October 14 at 10:30 am, etc.

At block 614, client computing device 302 automatically stores emailattachments to edge drive 380 for automatic backup to secondary storagesubsystem 118 apart from the email messages that carry the attachments.Accordingly, client computing device 302 recognizes that a particularemail message carries attachment(s); and stores a copy of eachattachment to edge drive 380, which is uniquely identified as a storagelocation subject to certain storage policies and procedures in system300. In some embodiments, client computing device 302 may replace theattachment in the email with a stub and pointer, or just a pointer, tothe location of the attachment on edge drive 380 or to a backup copy insecondary storage subsystem 118. In some alternative embodiment, theattachment will remain in the email and edge drive 380 will store a copyof it.

After block 614 ends, control may pass back to block 602 to processanother email thread identified by client computing device 302.

FIG. 7 depicts some salient sub-operations of block 604 in method 400.In general, block 604 is directed at client computing device 302 (e.g.,using content summarizer 352) analyzing the relative contentcontribution of individual emails in an email thread to generate athread content summary (see, e.g., thread summary 802 in FIG. 8).Notably, while the analysis may ignore, drop, or trim certain emailsand/or information therein, the original emails and the email threadremain intact. The processing described in the present block is directedat generating the thread summary, not at changing the thread or theindividual emails therein. A user who does not wish to review the threadsummary or who wishes to read the email thread may do so, e.g., usingthe inbox pane of email client application 310.

At block 702, client computing device 302 assigns a weight to each emailin the email-thread. Illustratively, the highest weights are assigned toinitial and most-recent emails, and the weight drops with proximity tothe chronological median of the email thread (i.e., the median positionin the chronologically-ordered thread which has as many emails before itas after it). The rationale here is that the early emails probably carryimportant information, such as reporting a problem or failure condition,asking and clarifying a question, etc., while recent emails carryimportant information about the current trend, status, resolution, ordisposition of the thread's subject matter; and hence these deservehigher weightings as compared to middle emails, which may containdigressions, outdated information, and/or “noise.” This approach toassigning email weights is illustrated by equation 1, which recites:Email Weight WE _(i) =|M(N)−i|+CWhere:

-   -   WE_(i)—weight of nth email in thread of N emails    -   N—number of emails in the present thread    -   M—chronological median of N emails in thread=1>M<N    -   C—positive constant, e.g., 1, to prevent a zero weight    -   i—chronological position of email in thread

Equation 1. Email Weight

Example email weights in a 199-email thread according to Equation 1include:

-   -   WE001=|100−1|+1=100    -   WE025=|100−25|+1=76    -   WE199=|100−199|+1=100

Example email weights in a 5-email thread according to Equation 1include:

-   -   WE001=|3−1|+1=3    -   WE002=|3−2|+1=2    -   WE005=|3−5|+1=3

Although the median (M) is illustratively used to distribute the emailweights here, other approaches may be taken by alternative embodiments.For example, rather than equally weighing emails that are equidistantfrom the median as shown in the examples above, an alternative approachmay over-weigh more recent emails and under-weigh older emails thatfollowed the first email in the thread. The rationale here is that themost recent emails may be the most interesting and relevant to theconsumer of the thread summary as compared to older emails. The readerof the thread summary may be interested primarily in the current trend,status, resolution, or disposition reached in the email thread.Accordingly, email weightings may be skewed depending on varyingrationales about the relationship between the thread position of anemail and its purported importance in crafting a thread summary. Asshown below, email weightings play a part in generating the threadsummary.

At block 704, client computing device 302 drops certain emails fromfurther analysis when they lack follow-up, i.e., excluding emails thatno one in the thread responded to. This operation depends on how manyemails are in the thread (per summarizer parameters 362), i.e., emailsare dropped in a large thread but not in a relatively short one, sincerelatively important information may be contributed by each of a just afew emails. The rationale here is that, in a relatively large emailthread, emails without follow-up are not considered worth a response bythe thread participants and therefore may not carry information worthreporting in the thread summary. An exception here would be the mostrecent email in the thread, which is generally highly weighted due tothe expectation that it carries important information about the currenttrend, status, resolution, or disposition of the thread's subjectmatter. In some alternative embodiments, no emails are dropped. In someembodiments, block 704 may be performed before block 702.

At block 706, having possibly dropped some emails from furtherconsideration, client computing device 302 goes on to “find thecontribution” of each remaining (non-dropped) email in the email-threadby performing blocks 708 through 714.

At block 708, client computing device 302 stems words by collapsingrelated words into one common or root word. This operation is needed fornormalizing words for further analysis downstream, e.g., to determineword weights, to determine sentence intersections, to find correspondingword frequencies in word-frequency table(s) 364, etc. For example, thewords “patent,” “patented,” and “patenting” are stemmed into a root word“patent.” Stemming is well known in the art. Stemming is also used increating word-frequency tables 364.

At block 710, client computing device 302 trims greetings, salutations,headers, footers, and signatures from each email in the thread. Therationale here is to further focus the analysis of the contentcontribution of each email by excluding non-substantive information,thus retaining the body of the email to be further analyzed.

At block 712, client computing device 302 ignores certain common or“stop” words (e.g., is, am, was, etc.). Stop words are described in moredetail elsewhere herein. For convenience, the email content that remainsafter blocks 708, 710, and 712 may be referred to herein as “substantivecontent” or as appropriate “substantive words.” By excluding stop words,the present content contribution analysis can further focus onsubstantive content.

At block 714, client computing device 302 assigns a weight to eachsubstantive word in the present email. Criteria may be based onword-frequency table 364, frequency in email and/or thread, etc. asdescribed in more detail below. At this point, substantive words gleanedfrom the email are given a weight or weighting which will ultimatelyaffect which sentences are chosen for the thread content summary. Oneapproach for assigning a weight of each word w in an email i based onthe word's “local” frequency within email i is illustrated by equation2A, which recites:Word Weight WWw _((i))=COUNTw(i)/K _(i) *WE _(i)Where:

-   -   WWw(i)—weight of a word w in a given email i    -   COUNTw(i)—word count, i.e., how many times the word w appears in        email i including all sentences in email i    -   K_(i)—number of substantive words in the present email i    -   WE_(i) is obtained from Equation 1

Equation 2A. Word Weight Using Local Word Count

An alternative approach to word weighting is to normalize the word'sfrequency by the number of emails in the thread N, instead of thesubstantive word count K within email i used above—resulting in afrequency of the word relative to other words in the thread. This isrecited in equation 2B:Word Weight WWw _((i))=COUNTw _((i)) /N*WE _(i)Where:

N—number of emails in the present thread

Equation 2B. Word Weight Using Thread Size

Example word weights for the stemmed word “patent” appearing in emails001, 002, and 005 in a 5-email thread according to Equation 2B:

-   -   WW“patent”(001)=50 counts/N emails*WE001=50/5*3=30 in email 001;    -   WW“patent”(002)=10 counts/N emails*WE002=10/5*2=4 in email 002;    -   WW“patent”(005)=5 counts/N emails*WE005=5/5*3=3 in email 005.

Yet another approach is to use, in either of the above word weightequations, the word frequency extracted from word-frequency table 364.Thus, the word weight in the present email may be biased according tothe frequency of the word in the training corpus that gave rise toword-frequency table(s) 364. For example, a high-frequency word in thetraining corpus (baseline set) may therefore weigh more in the presentemail i than a low-frequency word. The rationale here is to boost theword weight for words that occur frequently in the baseline windowperiod. Two examples of word weights biased from word-frequency table(s)364 are recited in equations 2C:Word Weight WWw _((i)) =fw*COUNTw _((i)) /K*WE _(i)Or:Word Weight WWw _((i)) =fw*COUNTw _((i)) /N*WE _(i)Where:

fw—frequency of word w in word-frequency table 364

Equation 2C. Word Weight Biased From Word-Frequency Table

In some alternative embodiments, only the words found in the “important”word-frequency table 364-IM are additionally boosted or biased using thefrequency value from the word-frequency table 364-IM, whereas “normal”words in 364-R are not boosted. Other approaches to assigning a wordweight are also possible in other alternative embodiments, withoutlimitation. The word weight is used later in scoring sentenceintersections.

At block 716, client computing device 302 generates a super-set ofsentences from the emails in the present thread. The superset ispreferably based on sentences comprising the substantive words that haveword weights assigned to them, i.e., “substantive sentences.”Accordingly, greetings, salutations, headers, footers, and signatureblocks that were trimmed at block 710 are also excluded from the presentsuperset.

At block 718, client computing device 302 calculates a score forpairwise sentence intersections that have one or more stemmed words incommon (or “intersecting words”). For any given pairwise intersection,the intersection score is based on the weights of the intersecting wordsand the weights of respective source emails. For example, if twosentences S1 and S2 have four words in common, e.g., the set of {w1, w2,w3, and w4}, the illustrative intersection score would be:

Intersection Score (S1∩S2)=—ΣWW{w1,w2,w3,w4}(001)*WE001+ΣWW{w1,w2,w3,w4}(002)*WE002Where:

{w1, w2, w3, w4} is the set of common words (intersection words) in thepair of sentences S1 and S2, e.g., {draft, figure, patent, application}

Sentence S1 is from email 001

Sentence S2 is from email 002

ΣWW{w1, w2, w3, w4}(001) is the sum of respective word weights WWw inemail 001 obtained from Equation 2A, 2B, or 2C

ΣWW{w1, w2, w3, w4}(002) is the sum of respective word weights WWw inemail 002 obtained from Equation 2A, 2B, or 2C, respectively

WE001, WE002 is the respective email weight from Equation 1

Equation 3A. Intersection Score

Word importance classification can be optionally used to bias theintersection score. Optionally, the word weights in the intersectionscore may be biased in favor of important words from word-frequencytable 364-IM. The rationale here is that words that are classified asimportant should raise the intersection score, which ultimatelyincreases the probability that the subject sentences comprising thoseimportant words will be chosen for the thread summary. For example:

Intersection Score (S1∩S2)=ΣWW{w1′,w2,w3,w4}(001)*WE001+ΣWW{w1′,w2,w3,w4}(002)*WE002Where:

w1 is a word found in the important word-frequency table 364-IM

w2, w3, w4 are words not found in the important word-frequency table

WWw1′(001) is a boosted word weight for word w1 in email 001, e.g.,WWw1(001) plus an extra 20%

WWw1′(002) is a boosted word weight for word w1 in email 002, e.g.,WWw1(002) plus an extra 20%

Equation 3B. Intersection Score with Bias for Word ImportanceClassification

Any boost scheme may be used here, e.g., doubling the word weight ofimportant words, adding a constant, etc., without limitation. Forexample, the boosted word-weights in Equation 3B may be alternativelyboosted based on the respective word's frequency in word-frequency table364:WWw1′(001)=WWw1(001)*fw1AndWWw1′(002)=WWw1(002)*fw1Where:

WWw1′(001) and WWw1′(002) are boosted word weights for word w/WW

w1(001) and WW w1(002) are word weights for word w1 from Eq. 2A or 2B

fw1—frequency of word w1 in word-frequency table 364

3B-1. Example Boosted Word Weights Based On Word-Frequency Table

At block 720, client computing device 302 composes a thread contentsummary based on relative content contribution from a set of uniquesentences forming the higher-scoring pairwise intersections, whichunique sentences are extracted from the superset of sentences in theemail thread, designated here SS. The J extracted unique sentences areordered chronologically, and their respective senders and timestamps areadded:Thread Summary TS={J sentences in chronological order ∈{highest-scoringintersections}}Where:

J is the number of unique sentences from the highest-scoring pairwiseintersections

Equation 4. Thread Summary

Thus, the thread summary illustratively comprises J sentences withattribution and timestamp. An illustrative thread summary 802 is shownin FIG. 8. J is a significantly reduced portion of the superset ofsubstantive sentences SS in the email thread chosen so that J sentencescan provide a proper summarization for the thread. Accordingly, J ispreferably defined in reference to the superset of sentences in theemail thread SS, such as for example:Thread Summary Sentences J=MAX(10,10% SS)orThread Summary Sentences J=MIN(15,MAX(30,5% SS))Where:

J<<SS

Equation 5. Size of Thread Summary

J may be defined as any number of sentences, whether a fixed number, orrelative to the number of sentences in the email thread as illustratedabove, or otherwise, e.g., based on how may emails are in the thread, N.

Equations 1, 2A-2C, 3A-3B, 3B-1, 4, and 5 are shown here forillustrative purposes, but it will be clear to those having ordinaryskill in the art, after reading the present disclosure, how to usevariations, combinations, and permutations of these equations forimplementing alternative embodiments of the present invention.Summarizer parameters 362 will include the appropriate subset ofEquations used in any given embodiment, e.g., Equations 1, 2A, 3A, 4,and 5.

FIG. 8 depicts an example screen shot of a user interface showing athread summary and an exemplary thread summary display pane. The leftside of the figure shows an email that may be part of a thread, andwhich is displayed in a manner well known in the art. The right side ofthe figure shows an illustrative thread summary 802, displayed withinits own distinct display pane according to the illustrative embodiment,e.g., via user interface 354. The thread summary display pane 801illustratively comprises thread summary 802, commitment/appointmentblock 803, and sentiment indicator 804.

Thread summary 802 is an example of an email-thread summary generatedaccording to the illustrative embodiment. The thread summary is based onrelative content contributions from the emails in the thread.

Commitment/appointment block 803 was described in more detail in regardto block 612. Although the depicted example in the present screenshot isdevoid of choices for a user to click, block 803 may show any number ofdate-time parameters from which the user may choose, and the choice thenpopulates a corresponding calendar entry.

Sentiment indicator 804 is based on processing the content of the emailsin the email thread and is meant to indicate the general sentimentgleaned therefrom, e.g., neutral, happy, angry, etc. Any number oftechniques are available in the art for generating a sentiment indicatorfrom emails, and one or more such techniques may be used here forgenerating sentiment indicator 804, e.g., integration with contentsummarizer 354, a library linked to content summarizer 352, etc.

The screenshot in the present figure is merely an example of how athread summary as disclosed herein may be presented to a user. Numerousvariations may be implemented by one having ordinary skill in the art,after reading the present disclosure, while remaining within the scopeof the present invention.

In regard to the figures described herein, other embodiments arepossible within the scope of the present invention, such that theabove-recited components, steps, blocks, operations, and/ormessages/requests/queries/instructions are differently arranged,sequenced, sub-divided, organized, and/or combined. In some embodiments,a different component may initiate or execute a given operation.

Example Embodiments

Some example enumerated embodiments of the present invention are recitedin this section in the form of methods, systems, and non-transitorycomputer-readable media, without limitation.

A1. A method for enhancing an email application to automatically analyzean email-thread and generate a content summary of the email-thread, themethod comprising:

identifying, by a computing device that executes the email application,the email-thread in the email application comprising a plurality ofemail messages;

generating the content summary of the email-thread, by the computingdevice, wherein the content summary is based at least in part on:

-   -   (i) an email-weight assigned to each email in the email-thread,    -   (ii) a word-weight assigned to certain words in each email in        the email-thread, and    -   (iii) an intersection-score assigned to identified intersecting        sentence pairs selected from sentences in the email messages in        the email-thread,        -   wherein the first sentence and the second sentence in a            respective intersecting sentence pair have a set of words in            common; and

wherein the content summary of the email-thread is based on relativecontent contributions by one or more email messages in the email-thread.

A2. The method of claim A1 wherein the email-thread is a fraction of thecollective size of the email messages in the email-thread.

A3. The method of claim A1 wherein the email-thread is a fraction of thecollective size of the email messages in the email-thread, wherein thefraction is defined according to a predefined formula which is based atleast in part on the number of email messages in the email-thread.

A4. The method of claim A1 wherein the email-weight assigned to eachemail in the email-thread is based on the chronological position of therespective email within the email-thread.

A5. The method of claim A1 wherein the respective word-weight assignedto certain words in each email in the email-thread is based on one ormore measures of frequency of the respective word in one or more emailsin the email-thread.

A6. The method of claim A1 wherein the intersection-score for arespective intersecting sentence pair is based on:

-   -   (a) word-weights of the set of words in common belonging to the        first sentence, weighted by the email-weight of the email        message comprising the first sentence.

A7. The method of claim A1 wherein the intersection-score for arespective intersecting sentence pair is based on:

-   -   (b) word-weights of the set of words in common belonging to the        second sentence, weighted by the email-weight of the email        message comprising the second sentence.

A8. The method of claim A1 wherein the intersection-score for arespective intersecting sentence pair is based on:

-   -   (a) word-weights of the set of words in common belonging to the        first sentence, weighted by the email-weight of the email        message comprising the first sentence, and    -   (b) word-weights of the set of words in common belonging to the        second sentence, weighted by the email-weight of the email        message comprising the second sentence.

A9. The method of claim A1 further comprising:

composing the content summary of the email-thread by listing inchronological order unique sentences chosen from the highest-scoringintersecting sentence pairs.

G1. A method comprising:

identifying, by a computing device that executes an email application,an email-thread comprising a plurality of email messages;

generating a content summary of the email-thread, by the computingdevice, wherein the content summary is based at least in part on:

-   -   (i) an email-weight assigned to each email in the email-thread        based on the chronological position of the respective email        within the email-thread,    -   (ii) a word-weight assigned to certain words in each email in        the email-thread based on one or more measures of frequency of        the respective word in one or more emails in the email-thread,        and    -   (iii) an intersection-score assigned to identified intersecting        sentence pairs selected from sentences in the email messages in        the email-thread,        -   wherein the first sentence and the second sentence in a            respective intersecting sentence pair have a set of words in            common, and        -   wherein the intersection-score for a respective intersecting            sentence pair is based on:            -   (a) word-weights of the set of words in common belonging                to the first sentence, weighted by the email-weight of                the email message comprising the first sentence, and            -   (b) word-weights of the set of words in common belonging                to the second sentence, weighted by the email-weight of                the email message comprising the second sentence; and

composing the content summary of the email-thread by listing inchronological order unique sentences chosen from the highest-scoringintersecting sentence pairs.

G2. The method of claim G1 wherein the content summary of theemail-thread is based on relative content contributions by one or moreemail messages in the email-thread.

M1. A method for summarizing a thread of emails, the method comprising:

identifying, by a computing device that executes an email application,an email-thread comprising a plurality of email messages;

for each email message in the email-thread:

-   -   (i) assigning an email-weight to the respective email message        based on the proximity of the respective email message to the        chronological median of the email-thread, and    -   (ii) assigning a word-weight to some words in the respective        email message,        -   wherein the word-weight is based on a frequency measure of            the respective word, and        -   wherein the word-weight is further based on the email-weight            of the respective email message comprising the respective            word;

identifying one or more intersecting sentence pairs selected fromsentences in the plurality of email messages in the email-thread,

-   -   wherein the first sentence in a respective intersecting sentence        pair has a second set of words in common with the second        sentence in the respective intersecting sentence pair;

assigning an intersection-score to each identified intersecting sentencepair, wherein the intersection-score is based on:

-   -   (a) word-weights of the words in the second set belonging to the        first sentence in the respective intersecting sentence pair,        weighted by the email-weight of the email message comprising the        first sentence, and    -   (b) word-weights of the words in the second set belonging to the        second sentence in the respective intersecting sentence pair,        weighted by the email-weight of the email message comprising the        second sentence; and

composing a summary of the email-thread by listing in chronologicalorder unique sentences chosen from the highest-scoring intersectingsentence pairs; and

causing the summary of the email-thread to be displayed to a user of thecomputing device.

M2. The method of claim M1 wherein the intersection-score assigned toeach intersecting sentence pair in the first set is further based onsumming:

-   -   (A) a first sum of the word-weights of the words in the second        set belonging to the first sentence in the respective        intersecting sentence pair, which first sum is weighted by the        email-weight of the email message comprising the first sentence,        and    -   (B) a second sum of the word-weights of the words in the second        set belonging to the second sentence in the respective        intersecting sentence pair, which second sum is weighted by the        email-weight of the email message comprising the second        sentence.

M3. The method of claim M1 wherein the email-weight for a given emailmessage negatively correlates to the proximity of the respective emailmessage to the chronological median of the email-thread.

M4. The method of claim M1 wherein a first email message that is closerto the beginning or end of the email-thread than a second email messagereceives a higher email-weight than the second email message.

M5. The method of claim M1 wherein the word score assigned to a givenword is higher when the word appears in a first word-frequency tablegenerated from emails that were classified as important, as compared towhen the word appears in a second word-frequency table generated fromemails that were classified as not-important.

ME1. A method for generating a content summary of a thread of emails,the method comprising:

identifying, by a computing device that executes an email application,an email-thread comprising a plurality of email messages;

assigning an email-weight to each email message in the email-thread,

-   -   wherein the email-weight negatively correlates to the proximity        of the respective email message to the chronological median of        the email-thread;

for each email message in the email-thread, assigning a respectiveword-weight to certain words in the respective email message,

-   -   wherein the word-weight is based on a frequency measure of the        respective word, and    -   wherein the word-weight is further based on the email-weight of        the respective email message comprising the respective word;

identifying a first set of intersecting sentence pairs selected fromsentences in the plurality of email messages in the email-thread,

-   -   wherein the first sentence in a respective intersecting sentence        pair has a second set of words in common with the second        sentence in the respective sentence pair;

assigning an intersection-score to each intersecting sentence pair,wherein the intersection-score is based on:

-   -   (a) a first sum of the word-weights of the words in the second        set belonging to the first sentence in the respective        intersecting sentence pair, which first sum is weighted by the        email-weight of the email message comprising the first sentence,        and    -   (b) a second sum of the word-weights of the words in the second        set belonging to the second sentence in the respective        intersecting sentence pair, which second sum is weighted by the        email-weight of the email message comprising the second        sentence;

selecting a third set of unique sentences from the highest-scoringintersecting sentence pairs; and

composing a summary of the email-thread by listing the selected thirdset of unique sentences in chronological order.

ME1a. The method of claim ME1 wherein the summary of the email-thread isbased on relative content contributions by one or more email messages inthe email-thread.

ME2. The method of claim ME1 further comprising:

before assigning the respective word-weight to certain words in eachemail message in the email-thread,

-   -   (i) stemming the certain words to a respective root word,    -   (ii) trimming one or more of headers, greetings, footers, and        signature blocks from each email message, and    -   (iii) ignoring predefined stop words in each email message,    -   thereby resulting in word-weights being assigned to words        designated as substantive words;

wherein the second set of words in any given intersecting sentence paircomprises only substantive words.

ME3. The method of claim ME1 wherein before identifying the first set ofintersecting sentence pairs,

ignoring email messages that lack a reply email message in theemail-thread,

except for the final email message in the email-thread.

ME4. The method of claim ME1 wherein the word-weight is based on afrequency measure of the respective word which measures how many timesthe respective word appears in the respective email message comprisingthe respective word as a function of the total number of words in therespective email message.

ME4a. The method of claim ME4 wherein the word-weight is furtherweighted by a second measure of frequency of the respective word in aword-frequency table which is based on email messages sent and receivedduring an earlier predefined baseline period of time.

ME5. The method of claim ME1 wherein the word-weight is based on afrequency measure of the respective word which measures how many timesthe respective word appears in the respective email message comprisingthe respective word as a function of the total number of email messagesin the email-thread.

ME5a. The method of claim ME5 wherein the word-weight is furtherweighted by a second measure of frequency of the respective word in aword-frequency table which is based on email messages sent and receivedduring an earlier predefined baseline period of time.

ME6. The method of claim ME1 wherein the first sum is further weightedby a second measure of frequency of the respective word in aword-frequency table which is based on email messages sent and receivedduring an earlier predefined baseline period of time; and

wherein the second sum is further weighted by the second measure offrequency of the respective word in the word-frequency table.

ME7. The method of claim ME1 further comprising:

before identifying the email-thread:

-   -   generating, by the computing device, a word-frequency table for        words found in a baseline set of email messages received and        sent during a predefined baseline period of time,        -   wherein the word-frequency table comprises a measure of a            frequency of occurrence of each word in the baseline set of            emails; and    -   wherein the measure of the frequency of occurrence of each word        from the word-frequency table is used in assigning the        word-weight to the respective word.

ME8. The method of claim ME1 further comprising:

before identifying the email-thread:

-   -   identifying a baseline set of email messages received and sent        during a predefined baseline period of time,    -   classifying, by the computing device, each email in the baseline        set of emails as either important or not-important,    -   generating a first word-frequency table for words designated as        important,        -   wherein the important words are found in the email messages            classified as important in the baseline set of emails,        -   wherein the first word-frequency table comprises a measure            of a frequency of occurrence of each important word in the            email messages classified as important, and    -   generating a second word-frequency table for words designated as        not-important, wherein the not-important words are found in the        email messages classified as not-important in the baseline set        of emails, and further wherein the not-important words are not        in the first word-frequency table,        -   wherein the second word-frequency table comprises a measure            of a frequency of occurrence of each not-important word in            the email messages classified as not-important;    -   wherein the measure of the frequency of occurrence of each        important word from the first word-frequency table is used in        assigning the word-weight to the respective important word; and    -   wherein the measure of the frequency of occurrence of each        not-important word from the second word-frequency table is used        in assigning the word-weight to the respective not-important        word.

ME9. The method of claim ME8 wherein the classifying, by the computingdevice, of each email message in the baseline set of email messages asimportant or not-important is based at least in part on one or more of:

-   -   (i) whether the respective email message is marked as read by a        user of the computing device executing the email application,    -   (ii) the elapsed time between the respective email message being        received and being responded to,    -   (iii) whether a follow-up flag was entered for the respective        email message, and    -   (iv) whether the respective email message is addressed        individually to the user.

ME10. The method of claim ME8 wherein an email message in the baselineset of email messages is more likely to be classified as important, bythe computing device, when one or more of:

-   -   (i) the respective email was read by a user of the computing        device executing the email application,    -   (ii) the user responded to the respective email message,    -   (iii) a follow-up flag was entered for the respective email        message, and    -   (iv) the respective email message was addressed individually to        the user.

TRN1. A method comprising:

identifying, by a computing device executing an email application, abaseline set of email messages received and sent during a predefinedbaseline period of time;

classifying, by the computing device, each email in the baseline set ofemails as either important or not-important,

-   -   wherein an email message is more likely to be classified as        important versus not-important, by the computing device, when        one or more of:        -   (i) the respective email message was read by a user of the            computing device executing the email application,        -   (ii) the user responded to the respective email message,        -   (iii) a follow-up flag was entered for the respective email            message, and        -   (iv) the respective email message was addressed individually            to the user;

generating a first word-frequency table for words in the email messagesclassified as important,

-   -   wherein the first word-frequency table comprises a measure of a        frequency of occurrence of each word in the email messages        classified as important;

generating a second word-frequency table for words in the email messagesclassified as not-important, which are not in the first word-frequencytable,

-   -   wherein the second word-frequency table comprises a measure of a        frequency of occurrence of each word therein in the email        messages classified as not-important;    -   wherein (a) the measure of the frequency of a given word stored        in the first or second word-frequency table, and (b) whether the        given word is in the first word-frequency table versus in the        second word-frequency table are factors used by the client        computing device to generate a content summary of an        email-thread comprising a plurality of email messages which are        distinct from and created after the baseline set of email        messages.

TRN2. The method of claim TRN1 further comprising:

for each email message in the email-thread:

-   -   (i) assigning an email-weight to the respective email message,        based at least in part on the proximity of the respective email        message to the chronological median of the email-thread, and    -   (ii) assigning a word-weight to some words in the respective        email message,        -   wherein for any given word the word-weight is based at least            in part on (a) the measure of the frequency of the given            word obtained from the first or second word-frequency table,            and (b) whether the given word is in the first            word-frequency table versus in the second word-frequency            table, and        -   wherein the word-weight is further based on the email-weight            of the respective email message comprising the respective            word.

TRN3. The method of claim TRN2 further comprising:

identifying a first set of intersecting sentence pairs selected fromsentences in the plurality of email messages in the email-thread,

-   -   wherein the first sentence in a respective intersecting sentence        pair has a second set of words in common with the second        sentence in the respective intersecting sentence pair;

assigning an intersection-score to each intersecting sentence pair inthe first set, wherein the intersection-score is based on:

-   -   (a) word-weights of the words in the second set belonging to the        first sentence in the respective intersecting sentence pair,        which are weighted by the email-weight of the email message        comprising the first sentence, and    -   (b) word-weights of the words in the second set belonging to the        second sentence in the respective intersecting sentence pair,        which are weighted by the email-weight of the email message        comprising the second sentence; and

generating the content summary of the email-thread by listing inchronological order unique sentences from the highest-scoringintersecting sentence pairs

MMG1. A computer-readable medium, excluding transitory propagatingsignals, storing instructions that, when executed by at least onecomputing device comprising one or more processors and computer-readablememory for storing the instructions, cause the computing device toperform operations comprising:

executing an email application;

identifying an email-thread comprising a plurality of email messages inthe email application;

generating a content summary of the email-thread, wherein the contentsummary is based at least in part on:

-   -   (i) an email-weight assigned to each email in the email-thread        based on the chronological position of the respective email        within the email-thread,    -   (ii) a word-weight assigned to certain words in each email in        the email-thread based on one or more measures of frequency of        the respective word in one or more emails in the email-thread,        and    -   (iii) an intersection-score assigned to identified intersecting        sentence pairs selected from sentences in the email messages in        the email-thread,        -   wherein the first sentence and the second sentence in a            respective intersecting sentence pair have a set of words in            common, and        -   wherein the intersection-score for a respective intersecting            sentence pair is based on:            -   (a) word-weights of the set of words in common belonging                to the first sentence, weighted by the email-weight of                the email message comprising the first sentence, and            -   (b) word-weights of the set of words in common belonging                to the second sentence, weighted by the email-weight of                the email message comprising the second sentence; and

composing the content summary of the email-thread by listing inchronological order unique sentences chosen from the highest-scoringintersecting sentence pairs.

MMG2. The method of claim MMG1 wherein the content summary of theemail-thread is based on relative content contributions by one or moreemail messages in the email-thread.

MM1. A computer-readable medium, excluding transitory propagatingsignals, storing instructions that, when executed by at least onecomputing device comprising one or more processors and computer-readablememory for storing the instructions, cause the computing device toperform operations comprising:

executing an email application;

identifying in the email application an email-thread comprising aplurality of email messages;

for each email message in the email-thread:

-   -   (i) assigning an email-weight to the respective email message        based on the distance of the respective email message from the        chronological median of the email-thread, and    -   (ii) assigning a word-weight to some words in the respective        email message,        -   wherein the word-weight is based on a frequency measure of            the respective word, and        -   wherein the word-weight is further based on the email-weight            of the respective email message comprising the respective            word;

identifying one or more intersecting sentence pairs selected fromsentences in the plurality of email messages in the email-thread,

-   -   wherein the first sentence in a respective intersecting sentence        pair has a second set of words in common with the second        sentence in the respective intersecting sentence pair;

assigning an intersection-score to each identified intersecting sentencepair, wherein the intersection-score is based on:

-   -   (a) word-weights of the words in the second set belonging to the        first sentence in the respective intersecting sentence pair,        weighted by the email-weight of the email message comprising the        first sentence, and    -   (b) word-weights of the words in the second set belonging to the        second sentence in the respective intersecting sentence pair,        weighted by the email-weight of the email message comprising the        second sentence;

defining a group of the highest-scoring intersecting sentence pairs; and

composing a summary of the email-thread that lists in chronologicalorder unique sentences from the group of highest-scoring intersectingsentence pairs.

MMT1. A computer-readable medium, excluding transitory propagatingsignals, storing instructions that, when executed by at least onecomputing device comprising one or more processors and computer-readablememory for storing the instructions, cause the computing device toperform operations comprising:

executing an email application;

identifying a baseline set of email messages received and sent in theemail application during a predefined baseline period of time;

classifying each email in the baseline set of emails as either importantor not-important,

-   -   wherein an email message is more likely to be classified as        important versus not-important, by the computing device, when        one or more of:        -   (i) the respective email message was read by a user of the            computing device executing the email application,        -   (ii) the user responded to the respective email message,        -   (iii) a follow-up flag was entered for the respective email            message, and        -   (iv) the respective email message was addressed individually            to the user;

generating a first word-frequency table for words in the email messagesclassified as important,

-   -   wherein the first word-frequency table comprises a measure of        frequency of        -   each word occurring in the email messages classified as            important;

generating a second word-frequency table for words in the email messagesclassified as not-important, which words also are not in the firstword-frequency table,

-   -   wherein the second word-frequency table comprises a measure of        frequency of each word therein occurring in the email messages        classified as not-important;    -   wherein (a) the measure of frequency of a given word stored in        the first or second word-frequency table, and (b) whether the        given word is in the first word-frequency table versus in the        second word-frequency table are factors used by the client        computing device to generate a content summary of an        email-thread comprising a plurality of email messages which are        distinct from and created after the baseline set of email        messages.

MMT2. The computer-readable medium of claim MMT1, wherein the operationsfurther comprise:

for each email message in the email-thread:

-   -   (i) assigning an email-weight to the respective email message,        based at least in part on the proximity of the respective email        message to the chronological median of the email-thread, and    -   (ii) assigning a word-weight to some words in the respective        email message,        -   wherein for any given word the word-weight is based at least            in part on (a) the measure of the frequency of the given            word obtained from the first or second word-frequency table,            and (b) whether the given word is in the first            word-frequency table versus in the second word-frequency            table, and        -   wherein the word-weight is further based on the email-weight            of the respective email message comprising the respective            word.

MMT3. The computer-readable medium of claim MMT3, wherein the operationsfurther comprise:

identifying a first set of intersecting sentence pairs selected fromsentences in the plurality of email messages in the email-thread,

-   -   wherein the first sentence in a respective intersecting sentence        pair has a second set of words in common with the second        sentence in the respective intersecting sentence pair;

assigning an intersection-score to each intersecting sentence pair inthe first set, wherein the intersection-score is based on:

-   -   (a) word-weights of the words in the second set belonging to the        first sentence in the respective intersecting sentence pair,        which are weighted by the email-weight of the email message        comprising the first sentence, and    -   (b) word-weights of the words in the second set belonging to the        second sentence in the respective intersecting sentence pair,        which are weighted by the email-weight of the email message        comprising the second sentence; and

generating the content summary of the email-thread by listing inchronological order unique sentences from the highest-scoringintersecting sentence pairs.

SY1. A system comprising:

a computing device for summarizing an email-thread, wherein thecomputing device is configured to:

-   -   identify an email-thread comprising a plurality of email        messages,    -   generate a content summary of the email-thread, wherein the        content summary is based at least in part on:        -   (i) an email-weight assigned to each email in the            email-thread based on the chronological position of the            respective email within the email-thread,        -   (ii) a word-weight assigned to certain words in each email            in the email-thread based on one or more measures of            frequency of the respective word in one or more emails in            the email-thread, and        -   (iii) an intersection-score assigned to identified            intersecting sentence pairs selected from sentences in the            email messages in the email-thread,            -   wherein the first sentence and the second sentence in a                respective intersecting sentence pair have a set of                words in common, and                -   wherein the intersection-score for a respective                    intersecting sentence pair is based on:                -    (a) word-weights of the set of words in common                    belonging to the first sentence, weighted by the                    email-weight of the email message comprising the                    first sentence, and                -    (b) word-weights of the set of words in common                    belonging to the second sentence, weighted by the                    email-weight of the email message comprising the                    second sentence, and    -   compose the content summary of the email-thread by listing in        chronological order unique sentences chosen from a group of        highest-scoring intersecting sentence pairs.

SY2. The system of claim SY1 further comprising:

a storage manager, in communication with the computing device, formanaging data storage operations in the system; and

wherein the computing device is further configured to:

-   -   receive from the storage manager one or more parameters used to        generate the content summary of the email-thread.

SY3. The system of claim SY2 wherein the one or more received parameterscomprise rules for the computing device to determine the number ofunique sentences for the content summary of the email-thread.

SY4. The system of claim SY2 wherein the one or more received parameterscomprise rules for the computing device to determine the email-weightassigned to each email message in the email-thread.

SY5. The system of claim SY2 wherein the one or more received parameterscomprise rules for the computing device to determine the word-weightassigned to certain words in each email message in the email-thread.

SY6. The system of claim SY2 wherein the one or more received parameterscomprise rules for the computing device to identify intersectingsentence pairs selected from sentences in the email messages in theemail-thread, and wherein the one or more parameters further compriserules for the computing device to determine the intersection-scoreassigned to respective identified intersecting sentence pairs.

SY7. The system of claim SY2 wherein the one or more received parametersindicate whether or not the computing device is to automaticallytransfer email attachments to a storage location subject to storageoperations managed by the storage manager; and

wherein the computing device is further configured to:

-   -   when the one or more received parameters so indicate,        automatically transfer email attachments to the storage location        subject to storage operations managed by the storage manager.

SY8. The system of claim SY1 further comprising:

a storage manager, in communication with the computing device, formanaging data storage operations in the system; and

wherein the computing device is further configured to:

-   -   receive from the storage manager one or more instructions to        participate in a storage operation for an attachment to an email        in the email-thread, wherein the storage operation comprises        backing up the attachment to a secondary storage device in the        system.

SY9. The system of claim SY1 wherein the content summary of theemail-thread is based on relative content contributions by one or moreemail messages in the email-thread.

SYS1. A system comprising:

a computing device for summarizing an email-thread, wherein thecomputing device is configured to:

identify an email-thread comprising a plurality of email messages;

for each email message in the email-thread:

-   -   (i) assign an email-weight to the respective email message based        on the proximity of the respective email message to the        chronological median of the email-thread, and    -   (ii) assign a word-weight to some words in the respective email        message,        -   wherein the word-weight is based on a frequency measure of            the respective word, and        -   wherein the word-weight is further based on the email-weight            of the respective email message comprising the respective            word;

identify one or more intersecting sentence pairs selected from sentencesin the plurality of email messages in the email-thread,

-   -   wherein the first sentence in a respective intersecting sentence        pair has a second set of words in common with the second        sentence in the respective intersecting sentence pair;

assign an intersection-score to each identified intersecting sentencepair, wherein the intersection-score is based on:

-   -   (a) word-weights of the words in the second set belonging to the        first sentence in the respective intersecting sentence pair,        weighted by the email-weight of the email message comprising the        first sentence, and    -   (b) word-weights of the words in the second set belonging to the        second sentence in the respective intersecting sentence pair,        weighted by the email-weight of the email message comprising the        second sentence; and

compose a summary of the email-thread by listing in chronological orderunique sentences chosen from the highest-scoring intersecting sentencepairs; and

cause the summary of the email-thread to be displayed to a user of thecomputing device.

SYS2. The system of claim SYS1 wherein the intersection-score assignedto each intersecting sentence pair in the first set is further based onsumming:

-   -   (A) a first sum of the word-weights of the words in the second        set belonging to the first sentence in the respective        intersecting sentence pair, which first sum is weighted by the        email-weight of the email message comprising the first sentence,        and    -   (B) a second sum of the word-weights of the words in the second        set belonging to the second sentence in the respective        intersecting sentence pair, which second sum is weighted by the        email-weight of the email message comprising the second        sentence.

SYS3. The system of claim SYS1 wherein the email-weight for a givenemail message negatively correlates to the proximity of the respectiveemail message to the chronological median of the email-thread.

SYS4. The system of claim SYS1 wherein a first email message that iscloser to the beginning or end of the email-thread than a second emailmessage receives a higher email-weight than the second email message.

SYS5. The system of claim SYS1 wherein the word score assigned to agiven word is higher when the word appears in a first word-frequencytable generated from emails that were classified as important, ascompared to when the word appears in a second word-frequency tablegenerated from emails that were classified as not-important.

In other embodiments, a system or systems may operate according to oneor more of the methods and/or computer-readable media recited in thepreceding paragraphs. In yet other embodiments, a method or methods mayoperate according to one or more of the systems and/or computer-readablemedia recited in the preceding paragraphs. In yet more embodiments, acomputer-readable medium or media, excluding transitory propagatingsignals, may cause one or more computing devices having one or moreprocessors and non-transitory computer-readable memory to operateaccording to one or more of the systems and/or methods recited in thepreceding paragraphs.

Terminology

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense, i.e., in the sense of “including, but notlimited to.” As used herein, the terms “connected,” “coupled,” or anyvariant thereof means any connection or coupling, either direct orindirect, between two or more elements; the coupling or connectionbetween the elements can be physical, logical, or a combination thereof.Additionally, the words “herein,” “above,” “below,” and words of similarimport, when used in this application, refer to this application as awhole and not to any particular portions of this application. Where thecontext permits, words using the singular or plural number may alsoinclude the plural or singular number respectively. The word “or” inreference to a list of two or more items, covers all of the followinginterpretations of the word: any one of the items in the list, all ofthe items in the list, and any combination of the items in the list.Likewise the term “and/or” in reference to a list of two or more items,covers all of the following interpretations of the word: any one of theitems in the list, all of the items in the list, and any combination ofthe items in the list.

In some embodiments, certain operations, acts, events, or functions ofany of the algorithms described herein can be performed in a differentsequence, can be added, merged, or left out altogether (e.g., not allare necessary for the practice of the algorithms). In certainembodiments, operations, acts, functions, or events can be performedconcurrently, e.g., through multi-threaded processing, interruptprocessing, or multiple processors or processor cores or on otherparallel architectures, rather than sequentially.

Systems and modules described herein may comprise software, firmware,hardware, or any combination(s) of software, firmware, or hardwaresuitable for the purposes described. Software and other modules mayreside and execute on servers, workstations, personal computers,computerized tablets, PDAs, and other computing devices suitable for thepurposes described herein. Software and other modules may be accessiblevia local computer memory, via a network, via a browser, or via othermeans suitable for the purposes described herein. Data structuresdescribed herein may comprise computer files, variables, programmingarrays, programming structures, or any electronic information storageschemes or methods, or any combinations thereof, suitable for thepurposes described herein. User interface elements described herein maycomprise elements from graphical user interfaces, interactive voiceresponse, command line interfaces, and other suitable interfaces.

Further, processing of the various components of the illustrated systemscan be distributed across multiple machines, networks, and othercomputing resources. Two or more components of a system can be combinedinto fewer components. Various components of the illustrated systems canbe implemented in one or more virtual machines, rather than in dedicatedcomputer hardware systems and/or computing devices. Likewise, the datarepositories shown can represent physical and/or logical data storage,including, e.g., storage area networks or other distributed storagesystems. Moreover, in some embodiments the connections between thecomponents shown represent possible paths of data flow, rather thanactual connections between hardware. While some examples of possibleconnections are shown, any of the subset of the components shown cancommunicate with any other subset of components in variousimplementations.

Embodiments are also described above with reference to flow chartillustrations and/or block diagrams of methods, apparatus (systems) andcomputer program products. Each block of the flow chart illustrationsand/or block diagrams, and combinations of blocks in the flow chartillustrations and/or block diagrams, may be implemented by computerprogram instructions. Such instructions may be provided to a processorof a general purpose computer, special purpose computer,specially-equipped computer (e.g., comprising a high-performancedatabase server, a graphics subsystem, etc.) or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor(s) of the computer or other programmabledata processing apparatus, create means for implementing the actsspecified in the flow chart and/or block diagram block or blocks. Thesecomputer program instructions may also be stored in a non-transitorycomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to operate in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the acts specified in the flow chart and/or blockdiagram block or blocks. The computer program instructions may also beloaded to a computing device or other programmable data processingapparatus to cause operations to be performed on the computing device orother programmable apparatus to produce a computer implemented processsuch that the instructions which execute on the computing device orother programmable apparatus provide steps for implementing the actsspecified in the flow chart and/or block diagram block or blocks.

Any patents and applications and other references noted above, includingany that may be listed in accompanying filing papers, are incorporatedherein by reference. Aspects of the invention can be modified, ifnecessary, to employ the systems, functions, and concepts of the variousreferences described above to provide yet further implementations of theinvention. These and other changes can be made to the invention in lightof the above Detailed Description. While the above description describescertain examples of the invention, and describes the best modecontemplated, no matter how detailed the above appears in text, theinvention can be practiced in many ways. Details of the system may varyconsiderably in its specific implementation, while still beingencompassed by the invention disclosed herein. As noted above,particular terminology used when describing certain features or aspectsof the invention should not be taken to imply that the terminology isbeing redefined herein to be restricted to any specific characteristics,features, or aspects of the invention with which that terminology isassociated. In general, the terms used in the following claims shouldnot be construed to limit the invention to the specific examplesdisclosed in the specification, unless the above Detailed Descriptionsection explicitly defines such terms. Accordingly, the actual scope ofthe invention encompasses not only the disclosed examples, but also allequivalent ways of practicing or implementing the invention under theclaims.

To reduce the number of claims, certain aspects of the invention arepresented below in certain claim forms, but the applicant contemplatesother aspects of the invention in any number of claim forms. Forexample, while only one aspect of the invention is recited as ameans-plus-function claim under 35 U.S.C sec. 112(f) (AIA), otheraspects may likewise be embodied as a means-plus-function claim, or inother forms, such as being embodied in a computer-readable medium. Anyclaims intended to be treated under 35 U.S.C. § 112(f) will begin withthe words “means for,” but use of the term “for” in any other context isnot intended to invoke treatment under 35 U.S.C. § 112(f). Accordingly,the applicant reserves the right to pursue additional claims afterfiling this application, in either this application or in a continuingapplication.

What is claimed is:
 1. A method comprising: classifying, by a computingdevice executing an email application, a baseline set of email messagesreceived and sent during a predefined baseline period of time, whereineach email message in the baseline set is classified as either importantor not-important; wherein a given email message in the baseline set ismore likely to be classified as important rather than not-important,when the given email message was addressed personally to a user of thecomputing device executing the email application, and not to a groupcomprising the user; by the computing device executing the emailapplication, generating a first word-frequency table comprising words inemail messages classified as important within the baseline set, whereineach word in the first word-frequency table is associated with a measureof frequency of occurrence of the word in the email messages classifiedas important; by the computing device executing the email application,generating a second word-frequency table comprising words in emailmessages classified as not-important within the baseline set, which arenot in the first word-frequency table, wherein each word in the secondword-frequency table is associated with a measure of frequency ofoccurrence of the word in the email messages classified asnot-important; by the computing device executing the email application,generating a content summary of an email-thread comprising a pluralityof email messages which are distinct from and created after the baselineset of email messages, wherein the content summary of the email-threadis generated based on, for each email message in the email-thread: (i)an email-weight assigned to the email message in the email-thread, basedat least in part on a proximity of the email message in the email-threadto a chronological median of the email-thread, and (ii) a word-weightassigned to some words in the email message in the email-thread, whereinfor any given word the word-weight is based at least in part on: (a) ameasure of frequency of the given word obtained from one of the firstword-frequency table and the second word-frequency table, (b) whetherthe given word is in the first word-frequency table versus in the secondword-frequency table, and (c) the email-weight of the email message inthe email-thread comprising the given word.
 2. The method of claim 1further comprising: by the computing device executing the emailapplication, identifying a first set of intersecting sentence pairs fromsentences in the email-thread, wherein a first sentence in a givenintersecting sentence pair has a second set of words in common with asecond sentence in the given intersecting sentence pair; and by thecomputing device executing the email application, assigning anintersection-score to each intersecting sentence pair in the first set,wherein the intersection-score is based on: (a) word-weights of thewords in the second set belonging to the first sentence in the givenintersecting sentence pair, which are weighted by the email-weight ofthe email message in the email-thread comprising the first sentence, and(b) word-weights of the words in the second set belonging to the secondsentence in the given intersecting sentence pair, which are weighted bythe email-weight of the email message in the email-thread comprising thesecond sentence.
 3. The method of claim 2 further comprising: by thecomputing device executing the email application, generating the contentsummary of the email-thread, which lists in chronological order uniquesentences from highest-scoring intersecting sentence pairs.
 4. Themethod of claim 1 wherein the given email message in the baseline set isfurther more likely to be classified as important rather thannot-important when the given email message in the baseline set was readby the user of the computing device executing the email application. 5.The method of claim 1 wherein the given email message in the baselineset is further more likely to be classified as important rather thannot-important when the user of the computing device executing the emailapplication responded to the given email message in the baseline set. 6.The method of claim 1 wherein the given email message in the baselineset is further more likely to be classified as important rather thannot-important when a follow-up flag was entered for the given emailmessage in the baseline set.
 7. The method of claim 1 wherein theword-weight for a given word is higher when the given word appears inthe first word-frequency table, as compared to when the given wordappears in the second word-frequency table.
 8. The method of claim 1further comprising: by the computing device executing the emailapplication, identifying a first set of intersecting sentence pairsamong sentences in the email-thread, wherein a first sentence in a givenintersecting sentence pair has a second set of words in common with asecond sentence in the given intersecting sentence pair; and by thecomputing device executing the email application, generating the contentsummary of the email-thread, which lists in chronological order uniquesentences from highest-scoring intersecting sentence pairs.
 9. Themethod of claim 1 further comprising: by the computing device executingthe email application, identifying a first set of intersecting sentencepairs among sentences in the email-thread, wherein a first sentence in agiven intersecting sentence pair has a second set of words in commonwith a second sentence in the given intersecting sentence pair; and bythe computing device executing the email application, assigning anintersection-score to each intersecting sentence pair in the first set,wherein the intersection-score is based on: (a) word-weights of thewords in the second set belonging to the first sentence in the givenintersecting sentence pair, and (b) word-weights of the words in thesecond set belonging to the second sentence in the given intersectingsentence pair.
 10. The method of claim 1 further comprising: by thecomputing device executing the email application, generating the contentsummary of the email-thread, which lists in chronological order uniquesentences from intersecting sentence pairs among sentences in theemail-thread, wherein a first sentence in a given intersecting sentencepair has words in common with a second sentence in the givenintersecting sentence pair.
 11. A non-transitory computer-readablemedium storing instructions that, when executed by a computing devicecomprising one or more processors and computer-readable memory, causethe computing device to perform operations comprising: executing anemail application; classifying a baseline set of email messages receivedand sent during a predefined baseline period of time, wherein each emailmessage in the baseline set is classified as either important ornot-important; wherein a given email message in the baseline set is morelikely to be classified as important rather than not-important when thegiven email message was addressed personally to a user of the computingdevice executing the email application, and not to a group comprisingthe user; generating a first word-frequency table comprising words inemail messages classified as important within the baseline set, whereineach word in the first word-frequency table is associated with a measureof frequency of occurrence of the word in the email messages classifiedas important; generating a second word-frequency table comprising wordsin email messages classified as not-important within the baseline set,which are not in the first word-frequency table, wherein each word inthe second word-frequency table is associated with a measure offrequency of occurrence of the word in the email messages classified asnot-important; generating a content summary of an email-threadcomprising a plurality of email messages which are distinct from andcreated after the baseline set of email messages, wherein the contentsummary of the email-thread is generated based on, for each emailmessage in the email-thread: (i) an email-weight assigned to the emailmessage in the email-thread, based at least in part on a proximity ofthe email message in the email-thread to a chronological median of theemail-thread, and (ii) a word-weight assigned to some words in the emailmessage in the email-thread, wherein for any given word the word-weightis based at least in part on: (a) a measure of frequency of the givenword obtained from one of the first word-frequency table and the secondword-frequency table, and (b) whether the given word is in the firstword-frequency table versus in the second word-frequency table, and (c)the email-weight of the email message in the email-thread comprising thegiven word.
 12. The non-transitory computer-readable medium of claim 11,wherein the operations further comprise: identifying a first set ofintersecting sentence pairs from sentences in the email-thread, whereina first sentence in a given intersecting sentence pair has a second setof words in common with a second sentence in the given intersectingsentence pair; and assigning an intersection-score to each intersectingsentence pair in the first set, wherein the intersection-score is basedon: (a) word-weights of words in the second set belonging to the firstsentence in the given intersecting sentence pair, which are weighted bythe email-weight of the email message in the email-thread comprising thefirst sentence, and (b) word-weights of words in the second setbelonging to the second sentence in the given intersecting sentencepair, which are weighted by the email-weight of the email message in theemail-thread comprising the second sentence.
 13. The non-transitorycomputer-readable medium of claim 12, wherein the operations furthercomprise: generating the content summary of the email-thread, whichlists in chronological order unique sentences from highest-scoringintersecting sentence pairs.
 14. The non-transitory computer-readablemedium of claim 11 wherein the given email message in the baseline setis further more likely to be classified as important rather thannot-important when one or more of: (i) the given email message in thebaseline set was read by the user of the computing device executing theemail application, (ii) the user responded to the given email message inthe baseline set, and (iii) a follow-up flag was entered for the givenemail message in the baseline set.
 15. The non-transitorycomputer-readable medium of claim 11 wherein the word-weight for a givenword is higher when the given word appears in the first word-frequencytable, as compared to when the given word appears in the secondword-frequency table.
 16. The non-transitory computer-readable medium ofclaim 11 wherein the operations further comprise: generating the contentsummary of the email-thread, which lists in chronological order uniquesentences from intersecting sentence pairs among sentences in theemail-thread, wherein a first sentence in a given intersecting sentencepair has words in common with a second sentence in the givenintersecting sentence pair.
 17. A computing device comprising one ormore processors and computer-readable memory, wherein the computingdevice is configured to: execute an email application; classify abaseline set of email messages received and sent during a predefinedbaseline period of time, wherein each email message in the baseline setis classified as either important or not-important; wherein a givenemail message in the baseline set is more likely to be classified asimportant rather than not-important when the given email message in thebaseline set was addressed personally to a user of the computing deviceand not to a group comprising the user; generate a first word-frequencytable comprising words in email messages classified as important withinthe baseline set, wherein each word in the first word-frequency table isassociated with a measure of frequency of occurrence of the word in theemail messages classified as important; generate a second word-frequencytable comprising words in email messages classified as not-importantwithin the baseline set, which are not in the first word-frequencytable, wherein each word in the second word-frequency table isassociated with a measure of frequency of occurrence of the word in theemail messages classified as not-important; generate a content summaryof an email-thread comprising a plurality of email messages which aredistinct from and created after the baseline set of email messages,wherein the content summary of the email-thread is generated based on,for each email message in the email-thread: (i) an email-weight assignedto the email message in the email-thread, based at least in part on aproximity of the email message in the email-thread to a chronologicalmedian of the email-thread, and (ii) a word-weight assigned to somewords in the email message in the email-thread, wherein for any givenword the word-weight is based on one or more measures of frequency ofthe given word in one or more email messages in the email-thread. 18.The computing device of claim 17 wherein for any given word theword-weight is based at least in part on: (a) a measure of frequency ofthe given word obtained from one of the first word-frequency table andthe second word-frequency table, (b) whether the given word is in thefirst word-frequency table versus in the second word-frequency table,and (c) the email-weight of the email message in the email-threadcomprising the given word.
 19. The computing device of claim 17 whereinfor any given word the word-weight is higher when the given word appearsin the first word-frequency table, as compared to when the given wordappears in the second word-frequency table.
 20. The computing device ofclaim 17 wherein the computing device is further configured to: generatethe content summary of the email-thread, which lists in chronologicalorder unique sentences from intersecting sentence pairs among sentencesin the plurality of email messages in the email-thread, wherein a firstsentence in a given intersecting sentence pair has words in common witha second sentence in the given intersecting sentence pair.